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Software Engineer - Triton
Salary Range: PLN Range: 260,400 - 352,200 About the job Build the framework support that helps AI developers unlock Graphcore hardware. You will help Graphcore accelerators work seamlessly with state-of-the-art ML frameworks, including Triton and PyTorch. Reporting to a Team Lead in Frameworks, you will design, implement, optimise and support critical software. Your work will shape how researchers and engineers use Graphcore hardware for demanding machine learning workloads. You will improve performance, quality and usability across a complex software stack. You will join our Triton team, delivering new features, reviewing code, writing technical documentation and working with upstream communities. You will also help coordinate open-ended technical work across teams. This is a role for engineers who want deep technical ownership and visible impact. As the ML software landscape evolves, you will keep learning and may contribute across other framework teams. The team and culture The Frameworks team connects Graphcore hardware with the tools ML engineers and researchers rely on. We work across PyTorch, Triton, JAX and TensorFlow, with a strong focus on usability and performance. Work happens through agile practices, close technical discussion and clear ownership. Engineers are trusted to speak up, solve hard problems and move work forward with pace. Decisions are shaped by evidence, code quality and business outcomes. You will collaborate across Graphcore and with open-source communities to deliver software that developers can trust. What we’re looking for · Strong software engineering skills, with the judgement to manage quality, complexity and technical debt. · Experience developing in Python and C++. · Experience in compiler development. · Ability to manage complex technical tasks with cross-team dependencies. · Clear communication skills, with a proactive approach to collaboration and technical leadership. · Interest in AI, ML frameworks, performance optimisation or computationally intensive engineering. While we have outlined a set of requirements, we value transferable skills and diverse experiences. If you meet most of our essential criteria, we encourage you to submit an application and showcase how your background makes you a strong candidate. Benefits · Flexible working: Balance your work and personal life with greater flexibility · Comprehensive healthcare and dental cover: Premium medical and dental insurance, with the option to extend cover to your family · Phantom equity: Share in Graphcore’s success · Fitness and wellbeing support: A fully funded Medicover gym card, giving you access to a wide range of gyms, fitness classes and leisure centres · Financial protection: Death and disability insurance, providing financial security for you and your loved ones · Retirement savings: Build your financial future, with a 4% employer contribution from Graphcore, alongside your own contributions · Employee Assistance Programme (EAP): Confidential advice and support for you and your family across a range of personal, financial and wellbeing matters We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We’re an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we’re happy to support you. Join the Team at Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute. If you want to shape the frameworks developers use to push AI compute forward, we’d love to hear from you. Apply now to be part of the journey.
Senior Software Engineer
Salary Range: PLN 260,000-352,000 Subject to alignment to the responsibilities and duties of the role About Graphcore At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence Job Summary We are looking for a senior engineer to design and evolve an application-level simulator for ML workloads that directly influences hardware and software architecture decisions. This role sits at the intersection of machine learning, systems, and hardware design. You will model real-world workloads, predict system behaviour, and provide insights that guide how our platform evolves. Success in this role requires not only strong technical depth, but also the ability to work closely with multiple teams to ensure the simulator reflects reality and drives meaningful decisions. The Team The Tenjin team focuses on building advanced simulation capabilities to model and predict the behaviour of large-scale ML workloads on next-generation hardware and software platforms. We operate at the intersection of machine learning, systems, and architecture, developing tools that enable data-driven decisions long before systems are fully built or deployed. Our work helps shape both hardware and software direction by providing early insights into performance, scalability, and efficiency. The team brings together engineers with backgrounds in simulation, ML systems, and computer architecture. We collaborate closely with ML engineers, performance teams, and silicon architects, but operate as an independent group focused on simulation as a core capability. Responsibilities and Duties - Design and evolve an ML application-level simulator that models workload execution, system behaviour, and resource usage - Translate real-world workloads and benchmarking data into accurate simulation models - Validate simulator outputs against real system measurements and continuously improve fidelity - Build scalable, maintainable components that support evolving hardware and software capabilities - Work closely with performance engineers, ML teams, and silicon architects to ensure the simulator reflects real use cases - Drive adoption of the simulator as a decision-making tool across the organisation Candidate Profile Essential: - Strong C++ development experience, especially in performance-sensitive or large-scale systems - Strong Python skills and familiarity with ML frameworks (e.g. PyTorch) and execution graphs - Solid understanding of computer architecture, memory hierarchy, and heterogeneous systems - Familiarity with ML accelerator concepts (e.g. tensor cores, compute tiles, high-bandwidth memory) Desirable - Understanding of modern ML architectures (e.g. transformers, MoE) in training and inference - Experience with simulators or performance models (hardware or distributed systems) - Knowledge of parallelism models and their mapping to hardware - Experience with profiling and debugging complex, multi-layer systems Benefits In addition to a competitive salary, Graphcore offers annual leave policy, medical and dental health plans, a gym card, and employee pension (matched up to 4%). We review our benefits on a yearly basis to ensure we offer a valuable and rewarding benefits programme to our employees. We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments.
PyTorch Engineer
About the job Help make Graphcore hardware feel native inside the ML frameworks engineers use every day. As a Software Engineer in our PyTorch team, you will help build the software that connects Graphcore accelerators with state-of-the-art machine learning frameworks. You will design, implement, optimise and support features across PyTorch, Triton and related technologies. Your work will help ML engineers and researchers get more from Graphcore hardware, without changing how they want to build. That means better compatibility, stronger performance and cleaner developer experiences. You will contribute to upstream PyTorch, support our hybrid Python and C++ extension, and help integrate compiler backend capabilities with torch.compile. You will learn fast, solve real engineering problems and build expertise in a large open-source ecosystem. The team and culture You will join the PyTorch team within Frameworks, working in a SCRUM team that ships features, reviews code, writes documentation and supports users. Work happens through clear ownership, practical decisions and close communication across software, AI/ML, research and hardware teams. The team values maintainable code, thoughtful design and curiosity about unfamiliar systems. Engineers are trusted to investigate, speak up and improve the codebase as they learn. This is a team for people who like open-source communities, complex technical problems and visible impact. You will move quickly, but with care for users and long-term quality. What we're looking for · Strong core software engineering skills and a collaborative team mindset · Experience developing Python libraries · Experience building performant C++ applications in a commercial setting · Understanding of linear algebra, floating-point arithmetic or numerical analysis · Confident using Git and reviewing code in a commercial team setting · Willingness to explore large, unfamiliar open-source codebases independently and with others Benefits · Flexible working: Balance your work and personal life with greater flexibility · Generous leave: Take time to rest, recharge and enjoy life outside of work · Retirement planning support: Up to 5% matched pension · Phantom equity: Share in Graphcore’s success · Workplace experience: Enjoy thoughtfully designed office spaces for collaboration, with free food and an on-site barista to support your day · Peace of mind protection: Income protection and life assurance to provide financial security for you and your loved ones · Flexible benefits: Tailor your benefits package with a choice of additional options, including private medical insurance and dental cover · Optional benefits: Dental cover, health cash plan, private medical insurance, cycle to work scheme, give as you earn We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We’re an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we’re happy to support you. Join the team at Graphcore Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute. If you want to help shape how PyTorch runs on Graphcore hardware, we’d love to hear from you. Apply now to be part of the journey.
Technical Program Manager, AI & Cloud Efficiency
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role: Glean is looking for a Technical Program Manager, AI & Cloud Efficiency to provide end-to-end oversight of these initiatives: maintain the portfolio, set priorities, drive the operating cadence, unblock owners, and ensure savings land. Glean delivers AI at enterprise scale across a deliberately open, provider-neutral stack. This breadth necessitates numerous efficiency initiatives running in parallel across engineering — token yield, compute right-sizing, LLM Gateway quotas, provider commitments to name a few. You will: - Drive Cloud and AI/LLM efficiency - Own a single, prioritised source of truth for all cost initiatives and drive them to measurable efficiency and margin gains. - Pressure-test savings claims: verify realised vs. projected savings post-launch, and prevent silent cost regressions from eroding prior wins - Build cost-attribution discipline: per-service, per-team, per-customer, per-feature tagging and allocation so every dollar has an owner - Oversee LLM spend across providers: procurement and commitment sizing - Govern internal AI tooling spend with per-user visibility, quotas, and value assessment - Build the observability & automation layer - Treat cost like production telemetry: real-time cost attribution, anomaly detection, alerting, and automated triage - Automate the toil: cost-triage agents, regression detection, and self-serve attribution so the program scales About you: - Deep, hands-on understanding of cloud infrastructure and AI/LLM economics - Proficient in driving efficiency, capacity, or FinOps-adjacent programs - Eng operations instincts: you think in SLOs, error budgets, telemetry, and postmortems, and you apply that discipline to spend - Strong SQL and data skills; you can query BigQuery, build a Sigma workbook, and model a scenario Location: - This role is hybrid (3 days a week in our Bangalore office) Compensation & Benefits: Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
Software Engineer, AI & Security
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role: Glean is looking for driven engineers to solve cutting edge problems in data and AI security and governance. In a rapidly growing startup, this entails empathizing with customer needs, understanding the problems and research in the domain to come up with novel solutions to challenging problems. Engineers are expected to develop ideas with product managers and designers to best balance engineering constraints with requirements, delivering intuitive experiences that enterprises can rely on to keep their users safe. You will: - Oversee the entirety of your greenfield features from inception to implementation, experimentation, launch and beyond - Provide leadership and mentor more junior engineers - Work with designers, product managers, data scientists, and other engineers to understand our problem space and create elegant solutions - Architect data pipelines, AI models, and REST APIs that are backed by stable, scalable server side implementations and maximize product flexibility for rapidly meeting evolving domain requirements - Write robust code that’s efficient, easy to read, maintain and test About you: - 5+ years of experience in product engineering - Experience developing enterprise security products - Experience in using AI/ML in the product - BA/BS in computer science, or related degree - Experience building and shipping scalable features across the frontend and backend - Thrive in a customer-focused, tight-knit and cross-functional environment - A proactive and positive attitude to lead, learn, troubleshoot and take ownership of both small tasks and large features - A user-centric and empathetic mentality for product development - Love authoring easy-to-hold and future-proof REST APIs, OpenAPI is a plus - Experience building distributed CRUD level functionality, ideally both SQL and NoSQL - Comfortable with or desire to master Golang, Java and TypeScript - Comfortable with effective use of AI tools for development Location: - This role is hybrid (4 days a week in our Mountain View office) Compensation & Benefits: The standard base salary range for this position is $140,000 - $265,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
Senior Technical Program Manager, Infrastructure
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role: Glean is seeking a Senior Infrastructure Technical Program Manager (TPM) to lead large-scale, cross-functional initiatives that define, scale, and optimize our infrastructure platform. This role sits at the intersection of infrastructure engineering, reliability, cost efficiency, and AI systems, driving programs that ensure Glean’s platform remains performant, scalable, and resilient as we continue to grow. You’ll partner closely with Infra, AI/ML, and Platform Engineering teams to design orchestration systems, streamline deployments, and build the foundations that power our search and AI capabilities. You’ll play a central role in: - Driving the company’s Infrastructure roadmap across Setup & Deployment, Runtime, Storage, and AI Infra. - Leading cross-functional programs that improve scalability, reliability, cost efficiency, and developer velocity. - Defining and orchestrating how Glean instances are deployed, upgraded, and monitored at scale. - Partnering with AI and Data teams to evolve our ML pipelines, model training infrastructure, and LLM serving stack. - Leading initiatives to improve observability, configuration management, and resource utilization. - Coordinating capacity planning, infrastructure migrations, and performance optimization programs. - Building clear visibility into infra cost drivers and partnering with finance and engineering leaders on optimization initiatives. You will: - Lead end-to-end infra programs spanning compute, networking, storage, orchestration, and AI workloads. - Partner with Engineering to define standards for environment provisioning, deployment automation, and configuration governance. - Develop and operationalize frameworks for runtime health, scaling, and disaster recovery. - Drive consistency and automation across deployment orchestration systems. - Establish clear metrics for reliability, performance, and cost efficiency. - Coordinate cross-team delivery of high-impact programs such as data pipeline scalability, LLM infrastructure expansion, or infra observability improvements. - Communicate program status and technical risks effectively to leadership and stakeholders. - Continuously identify process or system bottlenecks, and drive automation to improve speed and reliability of infra operations. About you: - BS/MS in Computer Science, Engineering, or a related technical field. - 8-10+ years of experience in technical program management, infrastructure, or SRE, with at least 3-5 years managing infra or platform-scale programs. - Proven success delivering cross-functional infrastructure programs in B2B or enterprise environments where scalability, uptime, and performance are critical. - Experience working closely with Infra, SRE, and ML/AI teams on distributed systems or data infrastructure. - Strong understanding of cloud infrastructure (AWS, GCP, or Azure) including compute, networking, storage, and orchestration systems. - Understanding of data pipelines, ML training workflows, and LLM runtime infrastructure is a plus. - Ability to structure complex multi-quarter infrastructure programs with clear milestones and measurable impact. - Strong written and verbal communication and ability to manage through ambiguity, anticipate scaling challenges, and align teams across priorities. - Builder mindset with focus on automation, reliability, and efficiency. Location: - This role is hybrid (4 days a week in our Mountain View office) Compensation & Benefits: The standard base salary range for this position is $198,000 - $235,500 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, gen erous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We’re committed to building and sustaining a diverse, inclusive workplace. We strive to attract and retain people with a wide range of backgrounds, experiences, and perspectives, and we do not discriminate on the basis of gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
Product Manager, Agent Security & Governance
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role: As a Glean Product Manager, you’ll help solve a ubiquitous problem that all knowledge workers in the world struggle with on a daily basis. You’ll deliver best-in-class products for finding, curating, sharing, discovering, and managing knowledge. We’ve only taken the first step towards our long-term vision of an intelligent work assistant, and we need great product leaders to take us the rest of the way. We’re currently a very lean product team, so you’ll have an outsized role in shaping both the product roadmap and the product team itself. You’ll collaborate closely with our stellar Design, Engineering, Sales, Marketing, and Success partners to understand our customers and build category-defining tools. You’ll wear many hats and gain both breadth and depth of experience. As Glean’s PM for Agent Security and Governance, you’ll develop new technologies and product features spanning explainable / transparent AI systems, identification and prevention of various vectors of AI risks, and the observability, security and privacy features around AI agents and underlying data for our customers. You will: - Spending a lot of time with our customers to deeply understand their knowledge needs - Developing key parts of our product roadmap, marrying customers’ needs with our product vision - Empowering your team by giving context, setting direction, and building alignment - Driving customer-focused decisions, clear prioritization, and efficient execution - Coordinating cross-functionally with with leadership, go-to-market teams, and other key stakeholders across the company - Building processes that will scale as our team and company go through rapid growth About you: - You have 8+ years of experience in product management at SaaS companies, primarily serving large enterprises with responsibilities spanning security, governance, trust, identity, data integrations. - You have a strong technical background and experience with both UX and API driven products, integration paths, and 3rd party product partnerships. - You are an excellent written and verbal communicator. - You have a proven track record of taking ownership, taking initiative, and delivering results. - You collaborate effectively with cross-functional partners. - You have a learning and growth mindset. - You are mission-first and understand that your success is measured by your product and team’s success. Location: - This role is hybrid (4 days a week in our San Francisco office) Compensation & Benefits: The standard base salary range for this position is $160,000 - $280,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
Founding Forward Deployed Engineer
About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company. About the Role: You'll join as a founding member of Glean's forward deployed team and operate with the autonomy and accountability of a founder. Your job is to discover and build Glean's next generation of product surfaces, working in a pod with Forward Deployed PMs directly with the C-suite of the world's most influential companies and with Glean's own engineering and product teams. Glean is a fully horizontal AI platform - and that scope is what makes this role unique. You won't be configuring existing products or optimizing within defined constraints. You'll identify the biggest unsolved business problems at our most strategic customers, build entirely new products to solve them, and in doing so shape what Glean becomes. The best of what you build ships to every Glean customer in the world. You get founder-level ownership with Glean's resources, relationships, and scale behind you. You will: - Discover and build Glean's next product surfaces: Your primary job is 0-to-1 product creation. Nothing about what you're building is predefined - you'll work with your FDPM to identify where Glean's platform can be extended to solve problems no product currently solves, then design and ship it. What you build becomes what Glean ships. - Lead deep opportunity discovery: Before you write a line of code, you go deep on the business. What's structurally broken? Where is the biggest concentration of unsolved value? What's actually buildable, and what's the fastest path to something real that can be tested and learned from? You'll form strong hypotheses alongside your FDPM and pressure-test them directly with the people who have to live with the outcome. - Be a technical partner to the C-suite: You'll earn trust at the highest levels of your customer organizations - not just with technical teams, but with the executives who are accountable for outcomes. You can explain what you're building, why it will work, and what the risks are to anyone in the room. - Scale what works Once something works, you'll make it repeatable - working closely with the core R&D team to ensure the product is scalable - Stay at the frontier with Glean's R&D team: You'll work closely with Glean's core engineering and product teams, staying ahead of what's possible on the platform and actively shaping how its capabilities evolve. What you encounter in the field directly informs what gets built next. About you: - You think like a founder. When you walk into a customer, you're curious about the business, digging into what's broken, and figuring out what to build that doesn't yet exist. You're scrappy and resourceful, you move fast enough to learn, and you're as comfortable in a strategic discussion with a CEO as you are deep in a codebase. You've shipped actual products that real people use, that drove real outcomes - and you want to do it at a higher level of ambition. - 0-to-1 build track record: You've built production software from scratch in ambiguous environments. You can point to something that didn't exist before you showed up and is now used by real people at scale. - Production AI experience: You've shipped AI-powered solutions in the real world - prompt engineering, agent development, evaluation frameworks, deployment at scale. Not just prototypes. - Full-stack technical depth: Strong programming skills across the stack with a deep understanding of and experience with how enterprise systems actually work. - Business acumen: You can walk into a customer, identify where the real problems are, and connect that diagnosis to a product hypothesis - without being handed a brief. - Customer instinct: You build trust quickly at every level of an organization, communicate with clarity, and know how to tailor your depth to the room. - Builder's judgment: You know what's actually buildable, how long it will take, and when to simplify scope to get something real into production faster. You spot problems early and solve them independently. - Curiosity and scrappiness: You're driven to understand problems deeply before solving them, and resourceful enough to find a path forward when none is obvious. - Experience: 4+ years in technical roles with a track record of shipping production software. Former technical founders are strongly encouraged to apply. - Willingness to travel: This role requires 25–50% travel. - Nice to Have: - Experience as a founder, at a top-tier technology company, or in a forward deployed engineering role. - A technical degree in CS, engineering, math, or a related field. - Deep familiarity with LLMs, retrieval systems, and evaluation frameworks. - Experience driving technology adoption inside large enterprises. Location: - This role is hybrid (3-4 days a week in one of our SF Bay Area offices) - This role requires 25-50% travel Compensation & Benefits: The standard range for this position is $160,000-$270,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. Special Note: This range encompasses varying levels of the role, you will be assessed for your level during the interview process. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy . By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement . By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement , and I agree to the terms.
Sourcer, AI Research & Engineering
ABOUT THE ROLE Genesis is a physical AI research lab and full-stack robotics company on a mission to unlock unlimited physical labor. We're building a universal robotics foundation model that unifies high-fidelity physics simulation, generative modeling, and large-scale real-world robot data. To get there, we need the best Research Scientists, SWEs, and Robotics engineers, and we're going head-to-head with the top AI labs to win them. It all starts at the top of the funnel: finding the people who aren't looking, and getting them to look. You're the front line of how Genesis wins talent. The quality of who we hire is capped by the quality of who you put in front of our team, and you'll be early enough to define how we source for years to come: the channels, the playbook, the tooling, the bar at the top of the funnel. WHAT YOU'LL OWN - Finding the people no one else can. Source elite Research Scientist, SWE, and Robotics/infra candidates who aren't on the market and have no reason to leave their current lab. Until your message lands. - Sourcing where the best actually are. Papers, GitHub, conferences, citation graphs, communities, networks, not job-board spray. You go find them, and you know how to read who's actually exceptional. - Outreach people answer. Write personalized, credible outreach that earns replies from senior researchers and engineers who ignore recruiters. You're the first impression of Genesis; make it sharp. - Building pipeline that converts. Map markets, build target lists, and keep healthy, calibrated pipelines moving for every active search. Hand recruiters and hiring managers candidates worth their time. - Building the machine. Stand up scalable, well-organized sourcing in Ashby, and automate the parts that don't need a human (list building, enrichment, sequencing) so you spend your time on judgment and outreach. YOU'LL THRIVE HERE IF - You've sourced senior, hard-to-win technical talent (engineering, AI/ML, or research) in a competitive market, and have the response rates to show for it. - You can read a technical profile and tell signal from noise: whose papers matter, whose GitHub is real, who's actually exceptional. - You write outreach that sounds like a human who did their homework, not a template. - You think in systems and automation: you'd build an AI workflow than run the same manual search twice. - You're a self-starter who brings structure to ambiguity and moves fast without dropping quality. - You read data well, including response rates, pipeline health, and where searches stall, and you adjust. BONUS POINTS - You've sourced Research Scientists, robotics, or deep-tech engineers specifically. - You've sourced across UK and France. - You've used AI tooling to genuinely speed up sourcing, and have opinions about what works. - You've been early at a startup and built something from zero. THE OFFER - Competitive base salary plus meaningful equity - Visa sponsorship and relocation support - Hybrid: 3-4+ days per week in our office - A front-row seat to one of the hardest, most important problems in AI, and the chance to build the sourcing engine behind it
Senior Annotation and Data Pipeline Manager
ABOUT GENESIS We are a full-stack general-purpose robot company, born across San Francisco and Paris and bound by a single mission: to make general-purpose robots a reality, unlocking infinite physical labor for the world and freeing people for creativity, exploration, and the pursuits they love for their own sake. We are French and American by birth and global by nature. We are backed by partners who share our vision, including Eclipse, Khosla Ventures, Bpifrance, and HSG, alongside Eric Schmidt, Xavier Niel, Daniela Rus, and Vladlen Koltun. Our people work across the Bay Area and Europe, building the engine that will teach robots to do real work in the real world. We recently unveiled Eno, our wheeled, dexterous robot powered by our GENE foundation model, and we are starting to put it to work with real customers. THE ROLE We have built a frontier model and put Eno in front of the world, fast. Behind that is a data engine: the machine that turns a raw human demonstration into data the model is measurably better for. This role owns that engine. A worn glove and a camera produce a raw demonstration, not training data. You will build the pipeline and the annotation operation that turn raw demonstrations into clean, labeled, training-ready data, and make it scale with automation rather than headcount. You will own the datasets, what gets annotated, and the ontology, how it gets labeled, bring vision-language models to bear on trajectory labeling and language grounding, and close the loop so the engine keeps making the model better. This role serves the whole operation, our own floors and our partner-funded collection. WHAT YOU'LL DO - Run the data engine. Own the loop from raw trajectory and video to training-ready datasets, with validation steps that guarantee clean, correctly labeled data. - Own datasets and ontology. Decide what gets annotated and how, designing the ontology with the model team for its training implications. - Automate with models. Use vision-language models for automated trajectory annotation, language grounding, and data synthesis, so the pipeline scales without linear headcount, while holding the quality bar. - Run the annotation operation. Stand up and scale labeling, internal and vendor, against a clear quality bar and a delivery schedule the model team can plan around. - Close the loop. Turn real-robot eval failures into targeted collection and annotation jobs, and prove the new data improves the model. - Own the metrics. Track inter-annotator agreement, label error rate, and throughput per annotator-hour, and drive them the right way. WHAT WE'RE LOOKING FOR - You have scaled an annotation or data pipeline at a serious operation. Four or more years in data or ML pipelines, including time leading the work. At a frontier AI lab or a top data operation, you have taken raw robot or embodied data to training-ready at volume and you know exactly where it breaks. The people who have done this are a small group. If you are one, we want to talk. - You can build, not just manage. Strong Python (Pandas, NumPy, PyTorch) and SQL. You write the automation that shrinks the pipeline. - ML literacy. You understand training versus test, precision and recall, and overfitting well enough to design an ontology that helps the model, not just labels data. - Hands-on technical leadership. You can run a labeling operation and stay a hands-on contributor at the same time. - Comfortable with ambiguity and speed. You move fast in a research-paced environment and bring order to it. HOW WE WORK We are always looking for people who are driven to work on hard problems and want to shape what the world will look like in ten years. A few of the values that guide us: - Limitless ambition. We hold ourselves to the highest bar in everything we build. - Relentless urgency. Iterate faster, learn faster. Time is the denominator. - Type-2 Fun. Take the work seriously, not yourself. Embrace the grind and find joy in the struggle. - Radical transparency. Candid communication builds trust, and direct feedback drives growth. - Multiculturalism. We come from across the world. Be curious. Meet people on their terms. - Team over ego. Help others, share context, and win as a team. - A joyful journey. We take pride in the craft, enjoy the ride, and make space to laugh. Happiness is part of how we get there.
Recruiter, AI Research & Engineering
ABOUT THE ROLE Genesis is a physical AI research lab and full-stack robotics company on a mission to unlock unlimited physical labor. We're building a universal robotics foundation model that unifies high-fidelity physics simulation, generative modeling, and large-scale real-world robot data. To get there, we need the best Research Scientists, SWEs, and Robotics engineers and we're going head-to-head with the top AI labs to win them. That's the job: making the best engineers turn down everyone else. You won't be doing it alone, but you'll be early enough to shape how we hire for years to come: the playbook, the bar, the tooling, the team. If you want to build a recruiting function rather than inherit one, keep reading. WHAT YOU'LL OWN - Closing elite technical talent. Full-cycle ownership of Research Scientist, SWE, and Robotics searches, from strategy through offer close, for candidates who are not on the market and have no reason to leave their current lab. Until you talk to them. - Being the leaders' recruiting brain. Partner with founders and engineering/research leaders as a real advisor: shape the search, calibrate the bar, push back when needed. - Sourcing where the best actually are. Papers, GitHub, conferences, communities, networks, not job-board spray. You go find them. - Running a process candidates rave about. Senior researchers judge a company by how it hires. Make ours sharp, fast, and human. - Building the machine. Stand up scalable sourcing, screening, and reporting in Ashby, and automate the parts that don't need a human so you spend your time on the parts that do. YOU'LL THRIVE HERE IF - You've closed senior, hard-to-win technical hires in engineering, AI/ML, or research, in a competitive market, full-360. - You can talk credibly with technical stakeholders and earn the trust of people who are skeptical of recruiters. - You think in systems and automation: you'd rather build a workflow (or an AI-assisted one) than do the same manual task twice. - You're a self-starter who brings structure to ambiguity and moves fast without dropping quality. - You read data well, including pipeline health, conversion, and where searches stall, and you adjust. BONUS POINTS - You've hired Research Scientists, robotics, or deep-tech engineers specifically. - You've recruited across UK, France, and US. - You've used AI tooling to genuinely speed up sourcing or screening, and have opinions about what works. - You've been early at a startup and built something from zero. THE OFFER - Competitive base salary plus meaningful equity - Visa sponsorship and relocation support - Hybrid: 3-4+ days per week in our office - A front-row seat to one of the hardest, most important problems in AI, and the chance to build the recruiting team behind it Genesis is an equal opportunity employer. The robots we build will serve everyone, and we're building a team that reflects that.
Director, Wet Lab Engineering
The Role: Generate Biomedicines is seeking a Director of Wet Lab Engineering to lead our multidisciplinary team in building the technologies that will define the next generation of experimental science. The team spans hardware, optics, microfluidics, automation, and software, and develops novel instruments, automated workflows, and integrated experimental systems that connect the physical laboratory with data, computation, and AI to accelerate the discovery and development of protein and biologic therapeutics. This is an exciting opportunity for someone who is deeply technical, creative, and a people-focused engineering leader who can help define the laboratory of the future and then build it . This leader will shape our vision for increasingly agentic laboratory operations, bringing together instruments, robotics, software, new assays and data types , and AI to enable experiments at unprecedented speed, complexity, and scale. The ideal candidate will have deep expertise in at least one physical engineering discipline, along with the technical breadth and judgment to lead across many others, recognize excellent engineering, and bring people and technologies into systems that are more powerful than their individual components. Importantly, Wet Lab Engineering is embedded within a highly technology-driven therapeutics organization, where the systems we build are not ends in themselves: enabling biological discovery, platform development, and therapeutic programs. We value leaders who are genuinely energized and engaged by biology and drug discovery, comfortable partnering closely with scientists, and able to understand the purpose behind an assay or workflow. The ideal leader will be motivated by seeing engineering translate into better experiments, faster learning, and ultimately better medicines. Here's how you will contribute: - Lead, develop, and grow a multidisciplinary team of engineers spanning hardware, optical, microfluidic, automation, and software engineering. - Set the technical vision for Wet L ab Engineering and identify opportunities where new engineering capabilities can fundamentally change how we do science. - Drive the development of bespoke instruments, automation, and integrated experimental systems from early ideas through deployed capabilities. - Advance our vision for increasingly autonomous and agentic laboratory operation, tightly connecting physical experimentation with software, data, and AI/ML. - Work side-by-side with wet-lab scientists, biologists, computational scientists, and ML teams to rapidly understand scientific needs and translate them into working systems, with a strong sense of urgency around shared platform development and pipeline execution goals. - Build a culture of creativity, technical excellence, rapid experimentation, and rigorous engineering. The Ideal Candidate will have: - A deeply technical engineering leader with 10+ years of relevant industry experience and a PhD or Masters degree in a physical engineering discipline, ; equivalent depth of research and industry experience will also be considered. - An inventive builder and systems thinker with a forward-looking perspective on experimental science, able to recognize opportunities where engineering can fundamentally change how science is done and energized by integrating instrumentation, automation, robotics, and other technologies into capabilities that do not yet exist. - A proven and excellent hands-on people manager with experience leading and developing multidisciplinary technical teams of 10-15 people , providing strong technical direction while creating space for domain experts to excel. - Familiar with the technologies, assays, and workflows used in biotechnology and drug discovery, particularly in protein and biologic research, and comfortable working closely with scientists across disciplines. - Possesses the technical range to engage meaningfully across hardware, automation, software, data, and AI/ML. - Ideally, brings experience in robotics and robotic system development. LI-HM1 About Generate:Biomedicines We are a clinical-stage generative biology company pioneering the AI revolution in drug design and development. We are advancing a new approach to drug creation—one grounded in the ability to design proteins with defined biological intent. By integrating machine learning with large-scale experimentation, this approach aims to reduce the uncertainty, time, and cost associated with developing protein-based medicines. Founded in 2018, we are advancing a growing pipeline of clinical and preclinical programs across multiple disease areas and protein modalities. By unifying computational design and clinical development within a single operating model, we translate this approach into clinical-stage programs and are leading a shift from traditional drug discovery toward systematic drug generation. At Generate:Biomedicines, we collaborate across disciplines in new ways to invent and innovate. We bring diverse perspectives to a shared goal of delivering better medicines to patients in need, faster, guided by our values and leadership behaviors. Generate:Biomedicines is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Recruitment & Staffing Agencies : Generate:Biomedicines does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Generate:Biomedicines or its employees is strictly prohibited unless contacted directly by the Company’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Generate:Biomedicines and the Company will not owe any referral or other fees with respect thereto. Compensation: The base salary range provided reflects our current estimate of what we anticipate paying for this position. Your actual base salary will be based on several factors, including job-related skills, experience, internal equity, relevant education or training, and market dynamics. In addition, you will be eligible for an annual bonus, equity compensation, and a competitive benefits package. Per Year Salary Range $189,000 - $284,000 USD
Software Engineer, Kernel Programming Model
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon. Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise. Key Responsibilities - PyTorch-Native Kernel Programming Model: Design the integration layer and runtime environments that enable custom kernels to execute as native extensions within the PyTorch ecosystem. - Virtual ISA: Implement architectural abstractions that resolve performance bottlenecks through direct hardware control while maintaining tensor-level programmability. - Kernel Developer Ecosystem: Build core programming tools, technical specifications, and reference implementations to enable seamless kernel development and community contributions. Minimum Qualifications - Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience. - Experience in systems programming such as Rust, C++, or Go with a deep understanding of computer architecture, including ISA, SIMD, and memory hierarchies. - Experience in designing and building clean, robust, and well-defined programming interfaces. Preferred Qualifications - Master’s or PhD degree in Computer Science or a related technical field, or equivalent practical experience. - Experience in designing low-latency asynchronous execution models, kernel-level performance optimizations, or hardware-software co-design. - Experience in programming language theory and compiler infrastructure, including the design of domain-specific languages or intermediate representations using frameworks such as LLVM or MLIR. - Experience in engaging the developer community through open-source contributions, technical evangelism, or managing developer ecosystems. Why Join FuriosaAI The defining bottleneck of the AI era is building the right hardware and software stack to run it at global scale. Furiosa is solving this challenge holistically from the ground up. With our flagship chip, RNGD, in mass production today and our next-generation platform in development with Broadcom, we are proving that full-stack, tensor-native compute is the future of AI infrastructure. This is a pivotal moment to join our team, right as we accelerate our global expansion. At Furiosa, you will: Solve AI’s Most Urgent Challenge. Help build the high-performance, energy-efficient inference hardware and software required to fulfill the promise of advanced AI. Pioneer Full-Stack Co-Design. Work with teams that are architecting solutions from silicon up through the compiler (featuring innovations like Tensor Contraction Language and Virtual ISA) and serving frameworks. Ship Real-World Silicon, Software, and Solutions. Turn breakthrough technology into commercial deployment. RNGD is in mass production with TSMC and running live enterprise workloads for global leaders like LG AI Research and Samsung SDS. Partner With the Industry's Best. Collaborate across an elite global ecosystem that includes TSMC, Broadcom, SK Hynix, and GUC. Do Your Life’s Best Work. Join a brilliant, low-ego, mission-driven team in a high-trust environment that values autonomy, intellectual curiosity, and shared ambition. Contact - recruit@furiosa.ai
Software Engineer, Kernel Programming
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon. Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise. About the Role Lead the integration of diverse AI models including VLA, Vision, and Multimodal architectures by utilizing our kernel programming language to ensure both accuracy and performance while keeping the stack ready for developers to use. Key Responsibilities - Design and implement efficient kernels on FuriosaAI’s kernel programming stack (including vISA, TCL), targeting Tensor Contract Processor (TCP) architectures. - Diagnose and optimize kernel performance with profiling tools and roofline analysis for each RNGD-accelerated AI model. - Develop and apply automated kernel generation and optimization for AI workloads. - Build diagnostic tools or testbeds for robust and reliable kernel validation. - Drive end-to-end programming enablement on RNGDs, creating reproducible guides and reference implementations. Minimum Qualifications - BS in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field. - Experience in low-level systems programming targeting XPU (e.g., NPU, GPU) architectures. - Experience collaborating across engineering, research, and product teams to align software development with product requirements. Preferred Qualifications - MS or PhD in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field. - Experience in optimizing high-performance kernels on AI accelerators (e.g., GPU, TPU) for AI products. - Understanding of XPU architecture (computation patterns, data movement) and software-hardware co-optimization strategies. - Experience in open-source or research projects on AI model architectures such as Diffusion, Mamba, and VLA. - Experience in designing efficient deep learning architectures and developing algorithms for AI applications. Why Join FuriosaAI The defining bottleneck of the AI era is building the right hardware and software stack to run it at global scale. Furiosa is solving this challenge holistically from the ground up. With our flagship chip, RNGD, in mass production today and our next-generation platform in development with Broadcom, we are proving that full-stack, tensor-native compute is the future of AI infrastructure. This is a pivotal moment to join our team, right as we accelerate our global expansion. At Furiosa, you will: Solve AI’s Most Urgent Challenge. Help build the high-performance, energy-efficient inference hardware and software required to fulfill the promise of advanced AI. Pioneer Full-Stack Co-Design. Work with teams that are architecting solutions from silicon up through the compiler (featuring innovations like Tensor Contraction Language and Virtual ISA) and serving frameworks. Ship Real-World Silicon, Software, and Solutions. Turn breakthrough technology into commercial deployment. RNGD is in mass production with TSMC and running live enterprise workloads for global leaders like LG AI Research and Samsung SDS. Partner With the Industry's Best. Collaborate across an elite global ecosystem that includes TSMC, Broadcom, SK Hynix, and GUC. Do Your Life’s Best Work. Join a brilliant, low-ego, mission-driven team in a high-trust environment that values autonomy, intellectual curiosity, and shared ambition. Contact - recruit@furiosa.ai
Software - Software Engineer, Compiler (Kernel Opt...
About FuriosaAI FuriosaAI builds high-performance, high-efficiency AI compute for the Inference Era. Founded in 2017 by veteran semiconductor and AI algorithm engineers, Furiosa operates globally with offices in Korea and Silicon Valley, along with a compiler-focused R&D lab in Lisbon. Our vision is to make AI computing sustainable, enabling access to powerful AI for everyone on Earth. We solve the AI hardware energy and operational cost crisis at the architectural level, rather than through brute force, building the world's first truly AI-native compute platform to unlock the full potential of artificial intelligence for every enterprise. About the Job The compiler plays a central role in FuriosaAI's mission to build high-performance, energy-efficient AI systems. Modern deep learning models are evolving rapidly and becoming increasingly diverse, making compilation a challenging problem. Transforming these models into efficient executable programs requires careful reasoning about complex transformations while preserving program meaning and structure. In this role, you will own the performance of critical AI kernels integrated into Furiosa-LLM, FuriosaAI's software stack for large language model serving. You will analyze end-to-end serving workloads, identify performance-critical bottlenecks, and implement highly optimized kernels using TCL (Tensor Contraction Language), FuriosaAI's programming language for kernel optimization. Because real-world serving workloads are inherently dynamic, you will develop scheduling, specialization, and algorithmic techniques that map them efficiently onto compiler abstractions and execution environments optimized for static workloads. Responsibilities - Analyze end-to-end LLM serving workloads and identify performance bottlenecks that can be addressed through kernel-level optimization. - Design, implement, and optimize high-performance kernels in TCL for critical operations in Furiosa-LLM. - Develop algorithmic techniques for efficiently supporting dynamic serving workloads. - Integrate, benchmark, and validate optimized kernels across representative models, input shapes, and serving scenarios. - Collaborate with compiler and serving teams to improve compiler capabilities and ensure optimized kernels work effectively within the production software stack. Minimum Qualifications - BS in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field. - Experience in developing low-level or performance-critical software. - Experience in analyzing performance bottlenecks using profiling, benchmarking, and hardware performance characteristics. - Understanding of parallel computation, memory hierarchies, and data movement on modern architectures. Preferred Qualifications - MS or PhD in Computer Science, Artificial Intelligence, Electrical Engineering, or a related field. - Experience in optimizing high-performance kernels on AI accelerators (e.g., GPU, TPU) for AI products. - Hands-on knowledge of kernel optimization techniques such as tiling, computation scheduling, operator fusion, memory layout transformation, vectorization, pipelining, and data movement optimization. - Experience reasoning about trade-offs among parallelism, memory bandwidth, on-chip memory capacity, compute utilization, and synchronization overhead. - Experience with accelerator programming or domain-specific kernel languages such as Triton, cuTile, or Pallas. Why Join FuriosaAI The defining bottleneck of the AI era is building the right hardware and software stack to run it at global scale. Furiosa is solving this challenge holistically from the ground up. With our flagship chip, RNGD, in mass production today and our next-generation platform in development with Broadcom, we are proving that full-stack, tensor-native compute is the future of AI infrastructure. This is a pivotal moment to join our team, right as we accelerate our global expansion. At Furiosa, you will: Solve AI’s Most Urgent Challenge. Help build the high-performance, energy-efficient inference hardware and software required to fulfill the promise of advanced AI. Pioneer Full-Stack Co-Design. Work with teams that are architecting solutions from silicon up through the compiler (featuring innovations like Tensor Contraction Language and Virtual ISA) and serving frameworks. Ship Real-World Silicon, Software, and Solutions. Turn breakthrough technology into commercial deployment. RNGD is in mass production with TSMC and running live enterprise workloads for global leaders like LG AI Research and Samsung SDS. Partner With the Industry's Best. Collaborate across an elite global ecosystem that includes TSMC, Broadcom, SK Hynix, and GUC. Do Your Life’s Best Work. Join a brilliant, low-ego, mission-driven team in a high-trust environment that values autonomy, intellectual curiosity, and shared ambition. Contact - recruit@furiosa.ai
Senior Software Engineer
ABOUT FREED: Doctors are overworked, burnt out, and are quitting in masses. At Freed, we combine clinician love with the latest AI tech and intense execution to create products that make clinicians happier. Our first product is an AI scribe that automates medical documentation. Since May of 2023, we have: - Acquired 26,000 paying and loving clinicians - Generated 100,000 patient notes daily and over 3 million monthly - Made thousands of clinicians happier https://love.getfreed.ai/b2xGQ1 With the backing of Sequoia Capital and other world-class VC’s, we are rapidly expanding our product offering. Patient-facing assistants, patient insights, EHR integrations, and other products are being built and used by thousands of clinicians every day. We are looking for entrepreneurs. Fast, ambitious, and smart individuals who want to take care of the people who care for our health. Expect intense, clinician-focused, and interesting co-workers who want to win. With an office in San Francisco, we embrace a hybrid schedule that brings out the best in teamwork and innovation. Our teams come together in person three days a week to collaborate, connect, and have a little fun along the way. ABOUT THE ROLE We're on the hunt for talented, high-caliber individuals to join our elite team of engineers. As part of our team, you'll play a pivotal role in restoring joy to medicine while pushing the boundaries of what's possible with AI technology. Our engineering culture emphasizes speed, end-to-end ownership, responsibility, and independence, attracting top-tier talent and promoting exceptional performance. HOW YOU’LL HAVE IMPACT - Full Stack: Take ownership of product features and drive implementation across the backend (TypeScript) and frontend (React/TypeScript) components of our software stack. - AI First: Adapt the latest AI models (language and speech) and techniques to our use case. You can contribute to any of: model training, fine-tuning, prompt engineering, and optimizing inference for latency and cost. Prior AI experience is not required. - Empowered Teams: Collaborate with team members in a fully remote work environment (work hours are flexible but most of the team is on the west coast). Our teams are autonomous and cross-functional, including Product Management and UX Design. - Data-driven: Design experiments to validate product changes and ensure the highest quality of our software. - Clinician Obsessed: Have a passion for our mission and dedication to making a positive impact on the healthcare industry. WHAT YOU’LL BRING - A history of consistent top performance and a desire for a mission-driven work culture. - 5+ years of experience in full stack Software Engineering. - Curiosity for LLM applications and familiarity with using AI for development (e.g. Copilot, ChatGPT, Cursor) - Familiarity with our tech stack is preferred, including React, TypeScript, NodeJS, Azure and SQL. WHAT WE WILL BRING - Competitive salary and equity in a high-growth company - Opportunity to make an immediate impact - Medical, dental, and vision coverage - Unlimited paid time off - Company-sponsored annual retreats - Commuter stipend for our San Francisco based employees - 401(k) plan to support your long-term financial goals
Social and Community Manager
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE The AI infrastructure industry moves faster than almost anything in tech. New models, benchmarks, and techniques land weekly, and the narrative around them forms in days or hours. We're hiring a Social and Community Manager who can read those waves, ride the ones worth riding, add signal to them, and start narratives of our own that catch and spread. This is a hands-on, execution-heavy role with judgment at its core. You'll decide what's worth reacting to, what we should say, and when. You'll back those calls with data, ship consistently across our social and community channels, and support marketing and product by turning a fast-moving field into content people actually want to share. KEY RESPONSIBILITIES Narrative & Trend Judgment Track conversations relevant to Fireworks in real time, judge what's worth jumping on versus noise, and move fast when a moment opens with a strong instinct for tone and timing. Frame narratives that give the community and market a reason to talk about Fireworks, not just one-off posts. Data, Analysis & Reporting Monitor social, Discord, and community platforms daily using analytics tools. Track the metrics that matter (engagement, reach, sentiment, growth, community health), turn them into clear reports, and use insights to recommend content changes, experiments, and next steps. Content Creation & Execution Create on-brand content informed by data, trends, and community feedback. Generate fresh formats that make technical AI topics shareable, own the social calendar, and ship consistently without losing the creative edge. Community Engagement Moderate discussions, answer questions, welcome members, and foster helpful conversations. Support and help run community programs (Champion/Ambassador initiatives, newsletters, AMAs, cohorts), and proactively spot ways to strengthen connections. Events & Cross-Team Collaboration Help plan and execute virtual and in-person events, webinars, and meetups, measuring impact to improve future ones. Keep calendars, trackers, and dashboards meticulously organized, and share data-driven insights with marketing, product, and engineering so efforts run smoothly and scale. WHAT WE’RE LOOKING FOR Must-Haves - 5-8 years of hands-on experience in social media management or community management (developer or AI communities preferred). - Sharp judgment on what's worth a reaction and what to ignore, plus a track record of content or narratives that actually traveled. - Strong excellence in data and analytics, you confidently track metrics, interpret performance, create reports/dashboards, and use insights to guide execution and optimization. - Self-starter mindset: comfortable proactively identifying trends and opportunities, then recommending actions or ideas to the team. - Creative thinker who generates fresh content ideas and approaches while staying on-brand. - Hands-on experience actively engaging and growing communities (Discord, Reddit, X, forums, etc.). - Experience with social and community analytics tools (native platforms + tools like Sprout Social or similar). - Meticulously organized with strong project management skills. - AI native, you use LLMs and generative AI tools daily and understand developer workflows around models and inference. - Strong execution skills: reliable, detail-oriented, and proactive in delivering high-quality work in a fast-paced environment. Nice-to-Haves - Experience supporting or contributing to community programs and events. - Familiarity with AI infrastructure or open-source model communities (e.g., Hugging Face ecosystem). - Basic video or multimedia production skills. - Background in fast-paced startup environments WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Senior Lifecycle Marketing Manager
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE OPPORTUNITY We're looking for a Lifecycle Marketing Sr. Manager to build and scale the customer journeys that power Fireworks' growth engine across both product-led and sales-led motions. This isn't a traditional CRM or email marketing role. It's a strategic growth role focused on delivering the right message, to the right audience, at the right time—whether they're a prospective buyer, self-serve developer, or enterprise customer. You'll own the strategy and execution of personalized lifecycle experiences across email, in-product messaging, web, AI-powered touchpoints, and sales- and customer success-enabled programs. Working closely with Product, Growth Marketing, Product Marketing, Sales, Customer Success, Engineering, and Data, you'll build intelligent customer journeys that nurture prospects, accelerate product adoption, deepen customer engagement, and drive long-term retention and expansion. You'll define how Fireworks communicate throughout the customer lifecycle using behavioral data, product usage, account insights, experimentation, and automation to create experiences that feel timely, relevant, and personalized. You'll also build lifecycle systems that continuously improve through AI, customer behavior, and experimentation. This is a foundational opportunity to build Lifecycle Marketing from the ground up at one of the fastest-growing AI infrastructure companies. WHAT YOU'LL BE DOING OWN THE LIFECYCLE STRATEGY - Design and own Fireworks' lifecycle strategy across the entire customer journey—from lead nurture and onboarding through activation, adoption, retention, expansion, and advocacy. - Build scalable lifecycle programs that accelerate pipeline, improve customer engagement, and drive long-term product adoption and revenue growth. - Develop lifecycle frameworks that support both self-serve (PLG) and enterprise (SLG) customer journeys. BUILD DEMAND GENERATION & CUSTOMER JOURNEYS - Build and optimize always-on nurture programs for net-new prospects, marketing-qualified leads, remarketable audiences, product users, and existing customers. - Create personalized experiences across email, in-product messaging, web, onboarding, product announcements, customer education, and AI-powered touchpoints. - Develop lifecycle messaging and content that is timely, relevant, and personalized based on where customers are in their journey. - Partner closely with Product, Sales, Customer Success, and Growth Marketing to deliver the right message through the right channel based on customer behavior, buying stage, product usage, and account signals. DRIVE PIPELINE, ADOPTION & EXPANSION Build lifecycle programs that help prospects and customers: - Nurture remarketable audiences into qualified pipeline - Re-engage inactive leads and dormant accounts - Successfully onboard new users - Reach activation milestones faster - Discover new models and platform capabilities - Increase product usage and consumption - Adopt additional products and features - Support enterprise sales and expansion opportunities - Improve retention and long-term customer value EXECUTE GTM & CUSTOMER COMMUNICATIONS - Own lifecycle communications supporting product launches, feature releases, GTM campaigns, customer announcements, and other high-impact business moments. - Partner with Product Marketing and Product teams to ensure messaging is timely, coordinated, and aligned across customer touchpoints. EXPERIMENTATION & OPTIMIZATION - Build a culture of experimentation across nurture campaigns, onboarding, messaging, customer education, and expansion programs. - Design experimentation frameworks that measure incremental business impact, optimize customer journeys, and inform future lifecycle investments. - Continuously improve lifecycle performance through A/B testing, behavioral insights, and data-driven optimization. AI & AUTOMATION - Leverage AI to improve personalization, content generation, segmentation, journey orchestration, and lifecycle decisioning. - Build intelligent lifecycle programs that dynamically determine who to engage, when to engage, where to engage, and what message to deliver based on behavioral, product usage, CRM, and account signals. - Evaluate emerging AI capabilities and automation tools that improve customer experience while increasing marketing efficiency. MEASUREMENT & INSIGHTS - Partner with Marketing Analytics and Data to establish lifecycle reporting, customer health metrics, and performance dashboards. - Measure performance across lead engagement, nurture effectiveness, activation, adoption, retention, expansion, pipeline influence, and revenue. - Translate insights into recommendations that continuously improve customer experiences and business outcomes. WHAT MAKES YOU A GREAT FIT - 8+ years of experience in Lifecycle Marketing, Customer Marketing, Growth Marketing, Product Marketing, CRM, or Product Growth within a high-growth B2B SaaS company. - Experience building lifecycle programs across both product-led and sales-assisted customer journeys. - Proven success developing nurture programs, onboarding experiences, customer engagement initiatives, and expansion campaigns that drive measurable business outcomes. - Hands-on experience with modern marketing automation platforms such as HubSpot, Marketo, Braze, Customer.io http://Customer.io, Iterable, or similar platforms. - Strong understanding of audience segmentation, lifecycle operations, email best practices, marketing automation, and customer journey orchestration. - Experience partnering cross-functionally with Product, Sales, Customer Success, Engineering, Product Marketing, and Analytics. - Strong analytical mindset with experience using experimentation, customer insights, and behavioral data to optimize lifecycle performance. - Excellent communication and content development skills with the ability to translate customer insights into scalable lifecycle strategies. - Comfortable building new systems, processes, and programs in fast-moving, ambiguous environments. BONUS POINTS FOR - Experience at a developer-focused, infrastructure, cloud, or AI platform company. - Experience supporting both PLG and enterprise sales motions. - Experience with product analytics platforms such as Amplitude, Mixpanel, Heap, or similar tools. - Familiarity with AI-powered personalization, agentic workflows, or LLM-driven customer experiences. - Experience supporting usage-based or consumption-based business models. - Experience with customer journey orchestration, experimentation, personalization, or CDP platforms. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Head of GTM Engineering & Systems
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. THE ROLE Our GTM team is growing 10x. As the leader of GTM Engineering you will set the architecture, drive our AI roadmap, or deliver on the auto-magical future that empowers every customer facing role. You'll own the full GTM tech stack: Salesforce, CPQ, enrichment, engagement tooling, and the connective tissue between systems serving a growing org of BDRs, AEs, SAs, and managers. You'll also be the person who brings agentic AI from concept to production for our GTM teams, not as an experiment, but as the new operating baseline. This is a builder and leader role. We're not looking for someone to manage vendors or coordinate rollouts. We want someone who will make hard architectural decisions, ship fast, and raise the bar for what great looks leading a GTM Engineering team. WHAT YOU'LL OWN 1. GTM TECH STACK AND AI FOUNDATIONS Own every tool the GTM organization runs on: Salesforce architecture, enrichment layer (Clay, Harmonic, Sumble), routing (LeanData), engagement (Gong, Lemlist, Granola), and the integrations between them. As we scale from roughly 50 to 300+ GTM team members, the architectural decisions you make now are the ones that compound. 2. QUOTING AND LEAD-TO-REVENUE ARCHITECTURE (0 TO 1) We don't have a real CPQ solution today. Deal approvals run through Slack, order forms are built in Google Docs, and the billing handoff is fragile. You'll build a durable quoting and lead-to-revenue architecture from scratch, whether that's native Salesforce CPQ, a purpose-built tool, or a custom solution. The goal: an AE can take a deal from pricing to signed order form without RevOps as a bottleneck. 3. AGENTIC WORKFLOWS FOR GTM TEAMS BDRs, AEs, SAs, sales managers, and RevOps are all under-leveraging AI today. You'll build the workflows that change that: AI-assisted account research, rep-facing deal intelligence, automated pipeline hygiene, manager insights. These should be workflows the team can't imagine working without, not demos. 4. BUILD AND SCALE THE GTM ENGINEERING TEAM You're inheriting two strong engineers. You'll grow from there: defining hiring profiles, setting technical standards, building career paths, and maintaining a culture where high-quality, fast-shipping work is the norm. MINIMUM QUALIFICATIONS - 10+ years in GTM Engineering, Revenue Operations, or Sales Operations at B2B companies; Consumption business model experience strongly desired - 5+ years of people management experience - Has architected in Salesforce at real depth: data model, process automation, integrations, governance — and knows how to take advantage of today’s modern CLI/MCP setups - Has driven real world sales rep productivity enhancements measured in $s not time saved. - Has built or rebuilt a quoting or CPQ workflow at meaningful scale - Has led a team and set technical direction, not just managed execution - Track record of building automation that sales reps actually use PREFERRED QUALIFICATIONS - Has shipped agentic or AI-native GTM workflows in production (not pilots) - Experience scaling GTM systems through a high-growth phase (Series B to D) - Familiarity with usage-based or consumption pricing models - Has worked at an AI/ML infrastructure, developer tools, or API-first company WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Head of Deal Desk
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. ABOUT THE ROLE As our Deal Desk Manager, you'll be the commercial backbone of our go-to-market motion — the trusted partner Sales turns to when structuring complex, high-value, and non-standard deals. You'll own deal structuring, pricing guidance, quoting, and the approval process end-to-end, quarterbacking across Sales, Finance, Legal, and Revenue Operations to get deals closed cleanly and quickly. Because Fireworks runs on both reserved and consumption pricing, you'll play a central role in shaping how we structure commits, tiers, and multi-year agreements in a rapidly evolving market. This is a foundational role for someone who wants to build scalable deal desk processes at a hypergrowth AI company. WHAT YOU'LL DO - Run deal desk: Manage the day-to-day operations of deal desk. Review and analyze deals that fall outside standard parameters (pricing, discounting, contract terms), manage the approval workflow, enforce approval thresholds, and drive fast, clear escalations to Finance leadership, Legal, and executive stakeholders. - Structure and optimize deals: Partner with Sales to structure complex, non-standard, and strategic deals — including consumption commitments, multi-year contracts, custom pricing, and enterprise terms. Be the go-to partner for account executives and sales managers for deal advisory, structuring deals that meet customer needs but protect Fireworks’ margins - Serve as pricing & policy subject matter expert: Set discounting frameworks and commercial policies. Partner closely with Product, Engineering, and Sales to propose new pricing models, SKUs, and packaging motions based on deal desk insights. - Build the function: Partner with Revenue Operations team to design a scalable deal desk system. Establish the playbooks, pricing guidelines, approval workflows, and exception-handling procedures. - Quarterback cross-functionally: Act as the connective tissue between Sales, Finance, Legal, Revenue Accounting, and Order Management — coordinating deal evaluation, negotiation support, and clean handoff from quote to bookable order. - Analyze deal economics: Model deal profitability, discount impact, and margin implications for consumption- and subscription-based structures to inform smart, data-driven deal decisions. - Validate bookings: Ensure deals are structured, quoted, and documented for clean booking and accurate revenue recognition, partnering closely with Revenue Accounting. - Report on what matters: Track and report on key metrics — deal cycle time, approval turnaround, deal quality/hygiene, discount and margin performance, and booking accuracy — and use them to continuously improve deal velocity. WHAT WE'RE LOOKING FOR - 7+ years in Revenue/Sales Operations, Sales Strategy, Finance, or a related analytical role at a high-growth technology company, with 3+ years specifically in Deal Desk - Hands-on experience structuring complex packaging quotes, including non-standard terms and custom pricing. - Strong understanding of consumption-based / usage-based pricing as well as subscription models — and how to structure commits, tiers, and multi-year agreements around them. - Comfortable being both the architect and operator - Solid financial modeling and analytical skills, with the ability to assess deal profitability, margin, and discount impact. - Excellent cross-functional communication and stakeholder management — you can influence without authority and keep Sales, Finance, and Legal aligned under deadline pressure. - Detail-oriented and process-driven, with strong instincts for building structure where none exists. - Proficiency with CRM (Salesforce) and CPQ tooling; comfort learning modern GTM/quote-to-order systems. - Bachelor's degree, or equivalent practical experience. NICE TO HAVE - Experience at an AI/ML, developer platform, or cloud infrastructure company, and familiarity with how companies buy AI/compute - Experience building or scaling a Deal Desk function from scratch at a Series B/C+ hypergrowth company (vs. inheriting a mature one) - Experience with modern CPQ platforms (e.g., Nue.io http://Nue.io) and contract lifecycle management (CLM) tools. WHO YOU'LL WORK WITH Sales & Sales Leadership, Finance & FP&A, Legal, Revenue Operations, Revenue Accounting, Order Management/Billing, and Product. WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
GTM Engineer
ABOUT US: Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI. We're hiring a GTM Engineer to help design, operate, and continuously improve the systems powering our revenue engine. This role sits at the intersection of GTM systems architecture and field execution — ensuring our tools, automations, and data flows are not only well designed, but actively driving productivity for our sales and marketing teams. You will work closely with sellers, marketers, and GTM leadership to ensure our systems surface the right signals, eliminate manual work, and help the team move faster. The Role Everything about the customer engagement workflow is changing - and the pace of change is faster than ever. You’re someone who wants to invent the sales platform of the future. Our goal is to have a simple and powerful agentic customer engagement experience that enables our sellers, solutions architects and team to win more business. You’re someone who wants to see world class AI applied to our go to market execution. You architect and operate the GTM tech stack — ensuring tools like Salesforce, HubSpot, Gong, Clay, Harmonic, LeadGenius, LeadIQ, and Zapier work together seamlessly. You build the one stop shop UI that harnesses the power of these tools and makes it easy for sales teams to use. You’ll design integrations, build automation, and ensure data flows cleanly across systems. Just as importantly, you'll partner directly with sellers to ensure the stack is actually helping them sell — improving workflows, removing friction, and ensuring signals translate into action. When reps struggle with tooling, workflows break, or valuable signals are missed, you step in to refine the system and make it better. What You'll Own GTM Systems & Integrations - Design and maintain the architecture of the GTM tech stack, ensuring tools across sales, marketing, and growth operate as a cohesive system - Build and maintain integrations across Salesforce, HubSpot, Gong, Clay, Harmonic, LeadGenius, LeadIQ, and Zapier - Design automation workflows that eliminate manual work, improve data quality, and accelerate pipeline velocity - Ensure enrichment data, engagement signals, and activity history flow across systems Seller Workflows & Tool Adoption - Partner closely with sellers and GTM leadership to ensure systems support real day-to-day selling workflows - Identify friction in the sales process and translate it into improved automation, tooling, or process design - Ensure reps are effectively using the GTM stack — from CRM hygiene to signal-driven workflows - Support onboarding and training for new sellers on how to leverage our tools and automation Data Integrity & Revenue Insights - Help maintain Salesforce as a clean, reliable system of record - Support the CRM data model, automation, and field governance to ensure consistent data capture - Ensure GTM systems produce trustworthy data that can power reporting and decision making - Build and maintain reporting that provides visibility into pipeline health, funnel performance, and campaign impact What We're Looking For - 5+ years in Revenue Operations, Sales Operations, or Marketing Operations at a B2B SaaS company - Strong experience working in Salesforce as an administrator or advanced user - Hands-on experience with modern GTM tools such as Salesforce, HubSpot, Gong, Clay, LeadGenius, LeadIQ, or Zapier - Experience designing workflows and automation that improve sales productivity - Comfortable working directly with sellers and translating operational needs into system improvements - Strong systems mindset — understanding how data, integrations, and workflows connect - Curious about new GTM tools and excited to experiment with AI-driven workflows WHY FIREWORKS? - Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving. - Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally. - Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results. - Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation. Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
Senior Software Engineer, 3D Computer Vision
Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications. Field AI is seeking a passionate Senior Software Engineer, 3D Computer Vision to play a vital role in the development of advanced algorithms for 3D reconstruction and spatial understanding. In this role, you will work with data from high-fidelity laser scanners and imaging sensors to design and optimize workflows for processing, analyzing, and structuring 3D point cloud datasets. The ideal candidate will have deep expertise in computational geometry and point cloud processing algorithms, delivering high-quality, maintainable code without necessarily requiring a background in robot hardware. Your contribution is essential to helping us extract precise geometric truths from the real world to ensure our continued growth and value. What You Get To Do: Develop and optimize point cloud processing pipelines, including registration, denoising, normal estimation, segmentation, and primitive extraction Design efficient algorithms for large-scale, unstructured 3D datasets with attention to memory and runtime performance Implement production-grade computational geometry and linear algebra in C++ and Python Solve complex reconstruction challenges such as loop closure, global consistency, and multi-view fusion Evaluate and integrate emerging 3D vision methods (e.g., neural implicit representations, advanced meshing techniques) Partner with platform teams to ensure scalable, efficient deployment of algorithms What You Bring: 4+ years of experience in Computer Vision, Computational Geometry, or 3D-focused Software Engineering Master’s or Ph.D. in Computer Science, Applied Mathematics, or related field with specialization in 3D vision or geometric processing Strong proficiency in modern C++ (C++14/17) and Python Solid mathematical foundation in 3D geometry, linear algebra, rigid body transformations (SE(3), quaternions), and projective geometry Deep experience with point cloud algorithms (ICP, GICP, RANSAC, NDT, region growing) and spatial data structures (k-d trees, octrees, voxel grids) Hands-on experience with libraries such as PCL, Open3D, Eigen, or Ceres Familiarity with common 3D data formats (PCD, PLY, E57, LAS) Strong problem-solving skills and ability to translate academic research into production-ready code What Sets You Apart: Experience with non-linear optimization frameworks (Ceres, GTSAM, g2o) for bundle adjustment or pose graph optimization Background in SLAM or Structure from Motion (SfM) pipelines Experience processing LiDAR, RGB-D, or photogrammetry datasets Familiarity with Linux development environments and containerization (Docker) Exposure to ROS (not required) Knowledge of survey-grade accuracy standards and georeferencing algorithms
AI Solutions Engineer (Fixed-Term)
FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. As an AI Solution Engineer at Field AI, you will work closely with strategic customers to ship production AI solutions that solve real business and operational problems. This role combines hands-on engineering, customer discovery, and product thinking to turn high-impact workflows into repeatable capabilities. If you thrive in fast-moving environments and enjoy owning outcomes from prototype to production, this role will put you at the center of customer adoption. What You'll Do Build and ship production AI features that deliver measurable customer value. Work directly with customer teams to understand workflows, pain points, and success criteria. Design and implement end-to-end solutions using Python and production LLM systems. Translate customer requirements into reusable product capabilities, not one-off custom work. Partner closely with Product, Research, and Engineering to prioritize and deliver high-impact features. Identify repeatable implementation patterns and codify them into internal playbooks. Travel to customer sites as needed (estimated around 10%) to accelerate deployment and adoption. What You Bring Bachelors degree or equivalent practical experience in software engineering, applied AI, or a related technical domain. Strong Python proficiency and experience shipping production-grade software. Experience with agentic systems, tool use, and workflow orchestration. Hands-on experience building and operating production LLM applications. Experience in customer discovery and translating business requirements into technical solutions. Strong problem-solving and communication skills across technical and non-technical audiences. High ownership mindset and ability to execute in ambiguous, cross-functional environments. Ability to travel to customer sites. What Sets You Apart Familiarity with model evaluation, quality measurement, and reliability practices. Background in forward deployed engineering, solutions engineering, or professional services. You have built side projects or products that solve real-world workflow problems.
Technical Accounting Lead, AI
fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products. As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on. ABOUT THIS ROLE: We're hiring a Technical Accounting Lead to own fal's technical accounting agenda, and support month end close, composed of technical and operational entries. The technical agenda includes nuanced revenue contracts, compute agreements, capitalized software, equity and stock-based compensation, consolidation and business combinations, expense classification, and the policies and operational application that support each. This is a hands-on, high-ownership role, with runway to lean on external technical accounting advisors as needed. You'll partner closely with Infrastructure, Procurement, Legal, Strategic Finance, and our external advisors, and use the latest AI tools to work productively. WHAT YOU'LL DO: - Execute our technical accounting agenda by working cross functionally and vertically throughout the organization to establish a rigorous technical accounting discipline - Work closely with business partners to articulate business requirements to operationalize technical conclusions - Assess the adequacy of current business systems and identify opportunities to leverage AI in your day to day work - Set a foundation of best practice internal controls considerations as you complete your technical tasks REVENUE (ASC 606) AND CONTRACT COSTS (ASC 340-40) - Research and advise on revenue accounting for customer contracts, including SSP & Principal/Agent analysis - Work cross-functionally with Sales, Legal, and Deal Desk on non-standard arrangements to determine appropriate application of GAAP accounting - Determine the appropriate GAAP application for our commission and incentive compensation plans COMPUTE COST ACCOUNTING - Research and document technical positions: lease vs. service contract, embedded leases, capitalization thresholds, impairment, and cost classification (COGS vs. opex vs. capex); write memos that stand up to auditor review - Evaluate accounting implications of new vendor agreements pre-signature, partnering with Legal and Infrastructure LEASES (ASC 842) & FIXED ASSETS - Own lease accounting across real estate, colocation space, GPU rental agreements, and equipment - Abstract new and modified contracts, assess classification (finance vs. operating), and identify embedded leases within compute and hosting arrangements - Accurately calculate lease liability, ROU asset, and expense amounts and prepare lease disclosures CAPITALIZED SOFTWARE (ASC 350) - Own internal-use software capitalization (ASC 350-40, including ASU 2025-06) — partnering with Engineering to assess which development activities qualify - Recommend and document capitalization and useful-life policies - Partner with Infrastructure on capex tracking, asset tagging, and periodic physical verification, and reconcile the fixed asset subledger to the GL EQUITY & STOCK-BASED COMPENSATION (ASC 718) - Support ASC 718 expense: award data reconciled to board minutes, 409A interpolation, award modifications, and secondary sales and tender offers, among other matters - Prepare and validate SBC calculations and disclosure reports CONSOLIDATION, BUSINESS COMBINATIONS & OTHER AREAS - Own consolidation across our US entity, foreign subsidiaries, acquired entities — including intercompany and FX - Own P&L expense classification, related-party analysis, going concern, and other technical positions as they arise - Research and document the company's positions under US GAAP, and draft and maintain the supporting policy memos QUALIFICATIONS/NICE TO HAVE: - Bachelor's degree in Accounting or Finance; CPA required - 8+ years of progressive accounting experience (tech, SaaS, cloud infrastructure, or AI strongly preferred), either direct from Big 4 with a technical focus on ASC 606, or a mix of Big 4 public accounting and in-house industry experience - Range of technical knowledge of US GAAP across ASC 606, ASC 842, ASC 718, ASC 350-40, ASC 805, ASC 810 - Experience supporting or leading an external audit - Strong written communication skills — you can translate complex accounting into clear, concise takeaways with non-technical audiences - High agency — you set your own priorities, make decisions independently, and drive work to completion - Experience at a high-growth software, cloud infrastructure, AI, or other capital-intensive technology company - AI and automation first. You use the latest AI tools — or build your own — to automate reconciliations, analyze large usage/spend datasets, and streamline your work WHAT WE OFFER AT FAL - Interesting and challenging work - A lot of learning and growth opportunities - We offer visa sponsorship and will help you relocate to San Francisco. - Health, dental, and vision insurance (US) - Regular team events and offsites COMPENSATION - $ 200,000 - $250,000 + equity + comprehensive benefits package U.S. EQUAL EMPLOYMENT OPPORTUNITY INFORMATION: fal provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other classification protected by applicable law.
Creative Technologist
fal is the generative media ecosystem powering the next generation of AI products. We build the infrastructure, tools, and model access that teams need to move from idea to production, and do it at scale without compromise. For developers and enterprises, fal is the foundation that makes generative media not just possible, but practical: a unified platform where high-performance inference, orchestration, and observability come together to unlock new categories of AI-native products. As generative media reshapes industries across a market projected to grow by hundreds of billions over the next decade, fal is becoming the ecosystem that ambitious teams build on. ABOUT THIS ROLE: We’re looking for a Creative Technologist who thrives at the intersection of design, engineering, and emerging technology. This role is equal parts builder, experimenter, and storyteller—someone who can prototype ideas quickly, explore new tools (especially AI), and turn abstract concepts into compelling, interactive experiences. You’ll collaborate across design, product, and engineering to bring ideas to life—from scrappy prototypes to polished demos—while pushing the boundaries of what’s possible. This role helps shape the future of our products and experiences by exploring what’s possible before it becomes obvious. You’ll act as a bridge between imagination and execution—turning ideas into things people can actually see, use, and feel. What you’ll do: - Prototype creative ideas rapidly using code, AI tools, and design software - Build interactive experiences, demos, and proof-of-concepts - Explore and integrate emerging technologies (e.g., generative AI, real-time media, webGL, creative coding) - Collaborate with designers and engineers to translate concepts into functional outputs - Develop internal tools or experiments that inspire new product directions - Contribute to storytelling through technical demos, visuals, and interactive content - Stay on top of new tools, frameworks, and creative trends Requirements/Nice to have: - Strong hybrid skillset across design + engineering - Proficiency in at least one programming language (JavaScript, Python, etc.) - Experience with creative coding, interactive media, or frontend development - Familiarity with AI/ML tools (e.g., generative models, APIs, or agent workflows) - A portfolio of creative technical work (interactive projects, prototypes, experiments) - Ability to move quickly from idea → prototype → iteration - Strong taste in design, UX, or visual storytelling - Experience with frameworks like Three.js, React, or WebGL - Background in motion design, 3D, or game engines - Experience working with APIs and backend systems - Familiarity with tools like TouchDesigner, Unity, Blender, or similar - Experience building with or integrating AI models (LLMs, diffusion, etc.) WHAT WE OFFER AT FAL - Interesting and challenging work - A lot of learning and growth opportunities - We offer relocation assistance to San Francisco. - Health, dental, and vision insurance (US) - Regular team events and offsites COMPENSATION - $150,000 – $210,000 + equity + comprehensive benefits U.S. EQUAL EMPLOYMENT OPPORTUNITY INFORMATION: fal provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other classification protected by applicable law.
Software Engineer (Safety)
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE TEAM Our National Security and AI Safety business unit is dedicated to advancing the responsible development and deployment of AI in support of national security and global stability. From strengthening mission-critical capabilities across national security and intelligence, to working with frontier labs to provide robust AI safety red teaming and evaluation, we work at the frontier of high-stakes, high-impact missions. We understand that powerful AI systems bring both transformative opportunities and complex risks and we are proud to partner with Government and the biggest tech organisations in the world to ensure AI is not just transformative but is also secure, trustworthy and safe for all. ABOUT THE ROLE Join us as a Software Engineer to deliver bespoke, impactful AI solutions for our diverse clients. You will bridge the gap between AI research and real-world impact by building scalable, production-grade machine learning systems. Partnering with clients and cross-functional teams, you will champion technical feasibility, ensure seamless delivery, and collaborate with Frontier Labs to reinforce our leadership in practical, high-stakes AI safety. WHAT YOU'LL BE DOING: - Building and deploying production-grade ML software, tools, and infrastructure. - Creating reusable, scalable solutions that accelerate the delivery of ML systems and capability testing of Frontier AI models. - Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges. - Leading technical scoping and architectural decisions to ensure project feasibility and impact. - Defining and implementing Faculty’s standards for deploying machine learning at scale. - Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders. WHO WE'RE LOOKING FOR: - You are comfortable building LLM applications, and are familiar with multi-agent harness tooling and AI Safety evaluation procedures. - You possess strong Python skills and solid experience in software engineering best practices. - You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security. - You've worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale - You are comfortable with core ML concepts, including probability, statistics, and common learning techniques. - You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. - You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders. - You thrive in a fast-paced environment, and enjoy the autonomy to own scope, solve and delivery solutions OUR INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Pair Programming Interview (90 minutes) 3. System Design Interview (90 minutes) 4. Commercial Interview (60 minutes) #LI-PRIO OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Senior Software Engineer (Safety)
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE TEAM Our National Security and AI Safety business unit is dedicated to advancing the responsible development and deployment of AI in support of national security and global stability. From strengthening mission-critical capabilities across national security and intelligence, to working with frontier labs to provide robust AI safety red teaming and evaluation, we work at the frontier of high-stakes, high-impact missions. We understand that powerful AI systems bring both transformative opportunities and complex risks and we are proud to partner with Government and the biggest tech organisations in the world to ensure AI is not just transformative but is also secure, trustworthy and safe for all. ABOUT THE ROLE As a Senior Software Engineer, we’ll look to you to lead development and deployment of cutting-edge AI systems for our diverse clients. You’ll design, build, and deploy scalable, production-grade ML software and infrastructure that meets rigorous operational and ethical standards. You will lead the bridge between AI research and real-world impact by architecting scalable, production-grade machine learning systems. Partnering directly with clients and cross-functional teams, you will drive technical strategy, mentor teams on best practices, and collaborate with Frontier Labs to define and reinforce our industry leadership in practical, high-stakes AI safety. WHAT YOU'LL BE DOING: - Leading technical scoping and architectural decisions for high-impact ML systems and capability testing of Frontier AI models - Designing and building production-grade ML software, tools, and scalable infrastructure - Defining and implementing best practices and standards for deploying machine learning at scale across the business - Collaborating with engineers, data scientists, product managers, and commercial teams to solve critical client challenges and leverage opportunities - Acting as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies - Mentoring and developing junior engineers, actively shaping our team's engineering culture and technical depth WHO WE'RE LOOKING FOR: - You have significant experience building and deploying secure and scalable LLM applications, and are comfortable with multi-agent harness tooling and AI Safety evaluation procedures. - You understand the full ML lifecycle and are confident operationalising models built with frameworks like TensorFlow or PyTorch - You bring deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems - You have demonstrable hands-on experience with cloud platforms (e.g., AWS, Azure, GCP) specifically cloud architecture, infrastructure management, and end-to-end cybersecurity practices - You've extensive experience working with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale - You thrive in fast-paced, high-growth environments, demonstrating ownership and autonomy in driving projects to completion - You communicate exceptionally well, confidently guiding both technical teams and senior, non-technical stakeholders OUR INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Pair Programming Interview (90 minutes) 3. System Design Interview (90 minutes) 4. Commercial Interview (60 minutes) #LI-PRIO OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Senior Machine Learning Engineer
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE TEAM Our Defence team is focused on building and embedding human-centered AI solutions which give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting-edge AI to high-stakes situations and maintain the balance of global powers essential to our liberty. Because of the nature of the work we do with our Defence clients, you will need to be eligible for UK Security Clearance (SC) and willing to work between 2 to 4 days per week on-site with these customers which may require travel to locations throughout the UK. When not required on client sites, you’ll have the flexibility to work from our London office or remotely from elsewhere within the UK. #LI-PRIO ABOUT THE ROLE As a Senior Machine Learning Engineer, we’ll look to you to lead development and deployment of cutting-edge AI systems for our diverse clients. You’ll design, build, and deploy scalable, production-grade ML software and infrastructure that meets rigorous operational and ethical standards. This is an ambitious, cross-functional role requiring a blend of technical expertise, engineering leadership, and confident client-facing skills. WHAT YOU'LL BE DOING: - Leading technical scoping and architectural decisions for high-impact ML systems - Designing and building production-grade ML software, tools, and scalable infrastructure - Defining and implementing best practices and standards for deploying machine learning at scale across the business - Collaborating with engineers, data scientists, product managers, and commercial teams to solve critical client challenges and leverage opportunities - Acting as a trusted technical advisor to customers and partners, translating complex concepts into actionable strategies - Mentoring and developing junior engineers, actively shaping our team's engineering culture and technical depth WHO WE'RE LOOKING FOR: - You understand the full ML lifecycle and have significant experience operationalising models built with frameworks like TensorFlow or PyTorch - You bring deep expertise in software engineering and strong Python skills, focusing on building robust, reusable systems - You have demonstrable hands-on experience with cloud platforms (e.g., AWS, Azure, GCP), including architecture, security, and infrastructure - You've extensive experience working with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale - You thrive in fast-paced, high-growth environments, demonstrating ownership and autonomy in driving projects to completion - You communicate exceptionally well, confidently guiding both technical teams and senior, non-technical stakeholders THE INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Pair Programming Interview (90 minutes) 3. System Design Interview (90 minutes) 4. Commercial Interview (60 minutes) OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Principal Machine Learning Engineer
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE ROLE As a Principal Machine Learning Engineer, you'll serve as the definitive technical authority on ML engineering across the organisation, setting the standard for how we design, build, and scale AI systems. You will own the architectural vision for our most complex and high-stakes programmes, influence engineering strategy at an organisational level, and act as a trusted partner to senior leadership and executive clients. This role goes beyond leading projects, you are a force multiplier who shapes the engineering culture, elevates the capability of those around you, and ensures our technical foundations are built to last. WHAT YOU'LL BE DOING: - Defining and owning the organisation-wide technical vision for ML engineering, establishing architectural standards and engineering practices that scale across teams and clients. - Overseeing the end-to-end delivery of flagship, business-critical ML programmes, spanning multiple workstreams, engineering teams, and client organisations. - Driving the strategic adoption of new technologies, platforms, and ways of working, influencing how the entire engineering craft evolves. - Cultivating senior engineering talent, coaching leads and managers, building capability pipelines, and embedding a culture of technical rigour and excellence. - Acting as the principal technical voice in C-suite and executive client engagements, shaping AI strategy and securing long-term strategic partnerships. - Leading on the most significant sales and pre-sales opportunities, providing architectural authority that differentiates our proposition and wins high-value engagements. - Partnering with Data Science, Commercial, and Infrastructure leadership to align ML engineering strategy with broader business goals and growth ambitions. WHO WE'RE LOOKING FOR: - You are a recognised ML engineering authority, able to go exceptionally deep across multiple domains and provide definitive technical judgement on the hardest problems. - You have mastery of Python and a proven track record of designing and operationalising production-grade ML systems at scale, across multiple frameworks and paradigms. - You are an expert across multiple major Cloud Solution Providers and have set the architectural direction for complex, full-stack AI platforms spanning multiple organisations. - You have deep expertise in containerisation, orchestration, and MLOps at scale, and have established the standards others follow. - You have a proven track record of developing senior engineering talent, coaching leads and managers, building capability, and shaping high-performance engineering cultures. - You have a visible external profile, through publications, conference contributions, open-source leadership, or industry influence, that reflects your standing in the field. - You operate naturally at the executive level, translating complex ML engineering decisions into commercial outcomes and proactively shaping the strategic direction of client engagements. OUR INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Introduction to the role (45 minutes) 3. Pair Programming Interview (90 minutes) 4. System Design Interview (90 minutes) 5. Commercial & Leadership Interview (60 minutes) OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Principal Data Scientist
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE TEAM In our Professional and Financial Services Business unit, we bring everything we have learned in more than a decade of Applied AI, and use it to help our clients navigate a rapidly changing landscape. We develop and embed AI solutions which help financial institutions become more efficient, enhance customer experience, and find the commercial upside in uncertain markets. Within the constraints of a highly regulated industry, we see so much opportunity for impactful innovation and are proud to set the gold-standard for marrying technical excellence with safe deployment. #LI-PRIO ABOUT THE ROLE As a Principal Data Scientist at Faculty, you will serve as a technical leader and domain expert who owns and drives the delivery of the most technically complex, high-impact projects and programmes for our most important clients. You also will set the technical direction for the data science team, mentor, and develop them so our data scientists remain best in class. This position focuses on deep individual contribution and technical excellence, influencing the broader data science community at Faculty. WHAT YOU'LL BE DOING: - Serving as a technical authority on machine learning, Generative AI, and other advanced data science methods to deliver innovative and impactful solutions. - Leading the development of shared resources, frameworks, and best practices adopted across teams and the company. - Contributing to the scoping and bid processes for large-scale, high-stakes projects, influencing client decisions with technical expertise. - Owning a portfolio of work within a specific sector, applying expert knowledge to deliver exceptional value to clients. - Leading and mentoring project teams and direct reports, ensuring the successful delivery of high-value and complex projects. - Acting as a thought leader, publishing papers, and presenting at industry and scientific conferences to amplify a distinctive AI vision for our clients WHO WE'RE LOOKING FOR: - You bring demonstrable technical ability, creativity and flexibility from your extensive experience (in academia , industry or both) as thought leader in this space - You’ll have prior experience working in or for financial services clients, with standout examples where you’ve led the delivery of distinctive applications that have driven commercial impact - You bring broad knowledge across a range of machine learning techniques, including experience building Generative AI and agentic AI applications with Large Language Models - You have advanced coding skills in Python and proven experience building and maintaining scalable codebases. - You enjoy mentoring junior colleagues and have prior direct management experience, inspiring them to continually stretch and grow their technical skill. - You are highly proficient in strategic problem-solving and communicating solutions to non-technical audiences, able to select appropriate solutions and balance innovation with practical implementation. THE INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Introduction to Business Unit Director (30 minutes) 3. Take Home Technical Assessment 4. Technical Interview (90 minutes) 5. Commercial & Principles Interview (90 minutes) OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Machine Learning Engineer
WHY FACULTY? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here https://faculty.ai/impact. We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence. Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology. AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. ABOUT THE TEAM Our Defence team is focused on building and embedding human-centered AI solutions which give our nation a competitive edge in the defence sector. We collaborate with our clients to bring ethical, reliable and cutting-edge AI to high-stakes situations and maintain the balance of global powers essential to our liberty. Because of the nature of the work we do with our Defence clients, you will need to be eligible for UK Security Clearance (SC) and willing to work between 2 to 4 days per week on-site with these customers which may require travel to locations throughout the UK. When not required on client sites, you’ll have the flexibility to work from our London office or remotely from elsewhere within the UK. #LI-PRIO ABOUT THE ROLE Join us as a Machine Learning Engineer to deliver bespoke, impactful AI solutions for our diverse clients. You will be instrumental in bringing machine learning out of the lab and into the real world, contributing to scalable software architecture and defining best practices. Working with clients, and cross-functional teams, you'll ensure technical feasibility and timely delivery of high-quality, production-grade ML systems. WHAT YOU'LL BE DOING: - Building and deploying production-grade ML software, tools, and infrastructure. - Creating reusable, scalable solutions that accelerate the delivery of ML systems. - Collaborating with engineers, data scientists, and commercial leads to solve critical client challenges. - Leading technical scoping and architectural decisions to ensure project feasibility and impact. - Defining and implementing Faculty’s standards for deploying machine learning at scale. - Acting as a technical advisor to customers and partners, translating complex ML concepts for stakeholders. WHO WE'RE LOOKING FOR: - You understand the full machine learning lifecycle and have experience operationalising models built with frameworks like Scikit-learn, TensorFlow, or PyTorch. - You possess strong Python skills and solid experience in software engineering best practices. - You bring hands-on experience with cloud platforms and infrastructure (e.g., AWS, Azure, GCP), including architecture and security. - You've worked with container and orchestration tools such at Docker & Kubernetes to build and manage applications at scale - You are comfortable with core ML concepts, including probability, statistics, and common learning techniques. - You're an excellent communicator, able to guide technical teams and confidently advise non-technical stakeholders. - You thrive in a fast-paced environment, and enjoy the autonomy to own scope, solve and delivery solutions OUR INTERVIEW PROCESS 1. Talent Team Screen (30 minutes) 2. Pair Programming Interview (90 minutes) 3. System Design Interview (90 minutes) 4. Commercial Interview (60 minutes) OUR RECRUITMENT ETHOS We aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations. If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours. A note on AI: we're happy for you to use it for research and interview prep, but please don't use it to generate answers during live interviews. We also use an AI note-taker (Metaview) in interviews so interviewers can stay present (which you can opt out of just let us know,) and every application is reviewed by a human, never decided by AI.
Research Engineer
ABOUT FACTORY Our mission is to create a world where software builds and improves itself. We build the platform for self-improving software development, helping the world's largest enterprise engineering teams turn their organizations into autonomous software factories. Customers including Nvidia, Blackstone, Royal Bank of Canada (RBC), Palo Alto Networks, Adobe, and T-Mobile run Factory to ship code, review PRs, run tests, and deploy continuously - getting smarter with every cycle. In 2026, we raised $200M at a $5B valuation, bringing our total funding to over $400M. We are backed by world-class investors and operators including Khosla Ventures, Sequoia, Blackstone, Ali Ghodsi (CEO of Databricks), and Frank Slootman (Former CEO of Snowflake). ABOUT THE ROLE Factory is seeking innovative Research Engineers to design and integrate advanced AI and ML capabilities that revolutionize productivity and accelerate innovation within software organizations. WHAT YOU WILL DO AND ACHIEVE - Design, develop, and deploy AI-driven agentic systems that enhance Factory’s core AI capabilities, focusing on retrieval systems, code generation evaluation, agentic user experience development, and agent backend architecture. - Collaborate with product and engineering teams to incorporate emerging AI research findings into practical, customer-centric solutions. - Engage in iterative development processes, rapidly prototyping and refining AI functionalities based on real-world feedback to meet the evolving needs of developers and enterprises - Take the initiative in identifying and addressing product stability and scalability challenges, ensuring our platform reliably support large-scale operational demands QUALIFICATIONS - 2+ years of hands-on experience in AI/ML engineering roles post-acquisition of a Bachelor's or Master's degree in Computer Science, Engineering, AI, or a related technical field. - Demonstrated proficiency with LLMs and a track record of applying AI/ML techniques to solve complex, unstructured problems, ideally within the domain of software engineering or related areas. - Self-motivated and autonomous, with a proven ability to navigate ambiguous research projects from conception to impactful deployment. - Strong communication skills that enable you to articulate technical concepts and strategies clearly at all levels, coupled with a strategic mindset oriented towards innovation. - Experience with data-intensive applications and familiarity with the software development lifecycle are highly desirable, though not mandatory. This is an in-office position (5 days/week) in San Francisco (walking distance to Caltrain)
RTL Design Engineer
About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary As an RTL Engineer at Etched, you will be critical in ensuring that our AI chips operate correctly and efficiently. You will develop and implement design verification strategies for both our existing and upcoming ASIC designs. In this role, you will work closely with state-of-the-art architectures for machine learning. You do not need to have experience working with these yet, but you will be willing and able to learn quickly. You will work in a fast-paced environment with a high degree of autonomy, and be responsible for a key part of Etched’s success. Representative projects - Implement a block to efficiently compute floating point math operators - Provide feedback to the uArch team to make sure blocks meet timing and area constraints You may be a good fit if you - At least 5 years of work experience in RTL development. - Experience with high-speed digital logic. - Proficiency in standard RTL design and synthesis tools - Familiarity with verification work and writing test benches - Are able to learn quickly about transformers and other aspects of modern artificial intelligence - Willing to start quickly Strong candidates may also have experience with (Nice-to-have qualifications) - Experience with PCIe, Ethernet, or HBM technologies - Familiarity with modern ML and LLM model architectures. - Familiarity with numerical representations and functions - Ability to program with Python or another scripting language We encourage you to apply even if you do not believe you meet every single qualification. Benefits - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $2.5k per month for those living within walking distance of the office - Relocation support for those moving to San Jose (Santana Row) - Various wellness benefits covering fitness, mental health, and more - Daily lunch + dinner in our office - Unlimited compute budget subject to ROI justification How we’re different: Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Inference Intern
About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary We are seeking talented Fall '26, Spring '27, and Summer '27 Inference Architecture interns to join our team and contribute to the design of next-generation AI accelerators. This role focuses on developing and optimizing compute architectures that deliver exceptional performance and efficiency for inference workloads. You will work on cutting-edge architectural problems and performance modeling over the course of your internship. Key responsibilities - Support porting state-of-the-art models to our architecture. Help build programming abstractions and testing capabilities to rapidly iterate on model porting. - Assist in building, enhancing, and scaling our runtime, including multi-node inference, intra-node execution, state management, and robust error handling. - Contribute to optimizing routing and communication layers using our collectives. - Utilize performance profiling and debugging tools to identify bottlenecks and correctness issues. - Develop and leverage a deep understanding of our architecture to co-design both HW instructions and model architecture operations to maximize model performance - Implement high-performance software components for the Model Toolkit You may be a good fit if you have - Progress towards a Bachelor’s, Master’s, or PhD degree in computer science, computer engineering, applied mathematics, or a related field - Proficiency in Python, C++ - Understanding of performance-sensitive or complex distributed software systems, e.g. Linux internals, accelerator architectures (e.g. GPUs, TPUs), Compilers, or high-speed interconnects (e.g. NVLink, InfiniBand). - Ported applications to non-standard accelerator hardware or hardware platforms. - Deep knowledge of transformer model architectures and/or inference serving stacks (vLLM, SGLang, etc.) Strong candidates may have some experience with - Proficiency in Rust - Low-latency, high-performance applications using both kernel-level and user-space networking stacks. - Deep understanding of distributed systems concepts, algorithms, and challenges, including consensus protocols, consistency models, and communication patterns. - Solid grasp of Transformer architectures, particularly Mixture-of-Experts (MoE). - Built applications with extensive SIMD (Single Instruction, Multiple Data) optimizations for performance-critical paths. - Familiarity with PyTorch or JAX. - Math competitions (AIME, AMC, etc) We encourage you to apply even if you do not believe you meet every qualification. Program details - 12-week paid internship - Generous housing support for those relocating - Daily lunch and dinner in our office - Based at our office in San Jose, CA - Direct mentorship from industry leaders and world-class engineers - Opportunity to work on one of the most important problems of our time For any questions, contact internships@etched.com. How we’re different Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Head of Inference Performance Visibility
About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary We are hiring a Head of Performance Visibility to define how performance is understood across next-generation AI accelerator systems. Our ML accelerator platform spans custom silicon, supercomputing software, compiler stacks, runtime libraries, and distributed inference environments. Performance at this scale is no longer a device-level question — it is a high-performance distributed system problem. You will define the performance metrics that connect raw hardware signals to distributed workload context, ML cluster dynamics, pod communication patterns, and emergent bottlenecks. This role requires more than telemetry. You will establish new abstractions, structured counter ontologies, cross-layer event correlation frameworks, distributed time-alignment strategies, and scalable reasoning systems operating across nodes, racks, and clusters. Working at the intersection of hardware design, driver architecture, runtime systems, and ML infrastructure, you will shape how these layers expose and consume performance intelligence. This is a foundational role defining not just tooling, but how our platform reasons about efficiency, scalability, and system behavior for years to come. Key Responsibilities besides Mentorship and Leadership System-Level Performance Design - Define the architectural approach for collecting and structuring telemetry across CPUs, drivers, interconnects, and multiple accelerators - Design scalable models for correlating performance events across device and host boundaries Cross-Layer Event Correlation - Develop mechanisms to align hardware counters, runtime activity, communication phases, and workload semantics across model-layer execution into coherent, actionable insight - Implement time synchronization and trace-alignment strategies across multi-device systems Telemetry & Counter Modeling - Define structured counter taxonomies separating base signals from derived metrics - Design derived performance models bridging low-level hardware signals and workload-level behavior - Influence instrumentation strategy for future hardware generations Distributed Performance Reasoning - Build tools that identify bottlenecks among multi-accelerator workloads across chips within hosts - Build cluster-scale performance analysis for distributed inference across data center networks Tooling & Insight Delivery - Contribute to analysis engines and developer-facing tooling that transform raw telemetry into intuitive insight - Shape how performance intelligence is surfaced to engineers debugging large-scale AI systems You may be a good fit if you have - Deep experience building complex systems at the intersection of hardware and software - Personally envisioned and built significant portions of profiling, tracing, or observability systems — not solely defined requirements or product strategy - Demonstrated ability to translate raw hardware signals into scalable, production-grade telemetry and analysis infrastructure - Experience correlating time-series events across distributed systems - Deep systems programming expertise (C++ or Rust), with a track record of shipping low-level infrastructure operating close to hardware or runtime systems - Experience designing distributed correlation mechanisms, timestamp-alignment strategies, or performance modeling frameworks across multiple devices or hosts - Experience designing distributed tracing or observability platforms at scale - Experience with high-performance computing systems and large AI training clusters - Experience with timestamp synchronization strategies and event alignment in distributed environments - Experience with hardware counter design and instrumentation strategy - Experience with performance modeling for large-scale ML workloads - Experience leading cross-functional architectural initiatives spanning hardware and software teams Benefits - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $2.5k per month for those living within walking distance of the office - Relocation support for those moving to San Jose (Santana Row) - Various wellness benefits covering fitness, mental health, and more - Daily lunch and dinner in our office - Unlimited compute budget subject to ROI justification How we’re different Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Strategic Projects Lead
About us Encord is the universal data layer for AI that helps 300+ AI teams train and run models on the right data. Our platform indexes, curates, annotates, and evaluates data across the full AI lifecycle, from development through production. Trusted by Woven by Toyota, AXA, UiPath, Zipline, and more. We're an ambitious team of 100+ working at the frontier of AI and have raised $60M in Series C funding from Wellington Management, CRV, Next47 and Y Combinator. The role As a Strategic Projects Lead, you'll fully own and optimize the data annotation and machine learning workflows behind Encord's largest client relationships. You'll work directly with clients, annotation specialists, ML engineers, Account Managers, and Forward Deployed Engineers to ensure the data powering their models is fast, accurate, and scalable. This is a hands-on, high visibility role. You have direct influence on whether Encord's highest-value customers renew and expand. What you'll do - Own data annotation projects end-to-end, translating complex AI/ML requirements into clear workflows and instructions for annotation teams - Design and refine annotation processes, audit results, and build feedback loops that raise data quality - Act as a trusted advisor to clients — designing and implementing the human-annotation workflow that gets them to production fastest - Partner with product and engineering to drive improvements in AI training data tools and methodology - Directly influence account health: your workflow design and execution are a primary driver of whether strategic accounts renew, expand, or churn Who we're looking for - A sharp, execution-oriented operator with a consulting or AI-company pedigree . A structured thinker, strong PM instincts, bias for getting things done - Analytically rigorous and comfortable with ambiguity. You break down operational problems from first principles - Technically fluent: comfortable querying a database, auditing annotation outputs, or automating a workflow in Python - A natural translator between ML engineers and non-technical clients on multi-stakeholder projects - Entrepreneurial — you take ownership without waiting to be told what to do Experience requirements - 3–7 years of professional experience, with a strong preference for backgrounds in top-tier strategy consulting and/or operations or data roles at leading AI or technology companies - Proven ownership of complex, multi-stakeholder workflows end-to-end: scoping, execution, QA, iteration - Experience designing/optimizing data operations with an eye for quality, consistency, and scalability, ideally human-in-the-loop or structured labeling work - Demonstrated ability to engage effectively with both technical stakeholders (ML engineers, data scientists) and non-technical clients, translating requirements clearly in both directions - Bonus: hands-on experience with computer vision, generative AI, or multimodal data workflows; prior exposure to data annotation platforms or quality management frameworks; experience coaching or managing operational teams - Bonus: Working proficiency in Python or SQL, with the ability to query data, automate workflows, or audit annotation outputs; broader familiarity with relational databases or data annotation tooling equally valued Why Encord - Competitive salary, commission, and meaningful equity in a high-growth start-up - Clear, accelerated growth opportunities as the company scales rapidly - Strong in-person culture: 4 days/week - Flexible PTO to fully recharge - Annual learning & development budget - Comprehensive health, dental, and vision coverage - Frequent travel opportunities across the U.S., London, and Europe - Bi-annual company offsites, twice-weekly team lunches, and monthly socials
Infrastructure Engineer
ABOUT ELICIT Elicit is an AI research assistant that uses language models to help researchers figure out what’s true and make better decisions, starting with common research tasks like literature review. What we're aiming for: 1. Elicit radically increases the amount of good reasoning in the world. - For experts, Elicit pushes the frontier forward. - For non-experts, Elicit makes good reasoning more affordable. People who don't have the tools, expertise, time, or mental energy to make well-reasoned decisions on their own can do so with Elicit. 2. Elicit is a scalable ML system based on human-understandable task decompositions, with supervision of process, not outcomes https://ought.org/updates/2022-04-06-process. This expands our collective understanding of safe AGI architectures. Visit our Twitter https://twitter.com/elicitorgto learn more about how Elicit is helping researchers and making progress on our mission. WHY WE'RE HIRING FOR THIS ROLE Elicit is an AI research platform used by scientists, pharma companies, and decision-makers for high-stakes evidence synthesis. A single session could trigger hundreds of thousands of language model invocations across multiple providers, which means our infrastructure decisions directly impact cost, reliability, and the quality of research outcomes for users making decisions worth millions of dollars. Our infra is well-architected using best practices — Terraform, Kubernetes, Argo CD, GitHub Actions. But we're at an inflection point: enterprise contracts are getting larger, single-tenant deployments are multiplying, and the surface area that needs dedicated attention has outgrown what our current team can cover part-time. This is the first dedicated infrastructure hire and you'll define how this function works at Elicit. James (Head of Engineering, ex-Square) set up the original infrastructure and will be your close partner. This role will own and evolve the infrastructure platform that underpins Elicit's product. You will ensuring it is reliable, secure, cost-efficient, and ready for the demands of a growing enterprise customer base. Under your ownership, our systems will scale gracefully across single-tenant deployments, our SLAs will be backed by real engineering rigor rather than best intentions, and our compliance posture will be a selling point rather than an afterthought. [https://app.ashbyhq.com/api/images/user-content/797554ae-ec94-4cd4-8a92-0ca2488582e0/d389e684-948e-434b-832d-9e3185875588/elicit-team-1.jpeg] WHAT YOU'LL OWN - Own our cloud infrastructure across AWS and GCP — Kubernetes clusters, networking, databases (Aurora PostgreSQL, Redis, MongoDB Atlas), Cloudflare, and our CI/CD pipeline. - Scale single-tenant deployments from a handful to many — each with distinct data retention, geographic, monitoring, and compliance requirements. Make a private cloud deployment a repeatable, low-overhead operation. - Build our observability and incident response practice — proactive monitoring, alerting, SLA tracking, and structured post-mortems that make the whole team better at diagnosing and resolving issues. - Drive compliance and security operations — ensure we follow through on the policies we've written (SOC 2, NIST AI framework, EU Cyber Resilience). Own disaster recovery exercises, database restoration drills, and security event monitoring (SIEM). - Manage infrastructure cost and capacity — make smart decisions about where we run workloads (AWS, CoreWeave, Parasail), optimize spend, and plan capacity as usage grows. - Improve developer experience — CI/CD pipeline performance, preview environments, local development tooling, and deployment confidence. - Contribute to backend systems where infrastructure and application intersect — circuit breakers, inference routing, data connector infrastructure for enterprise customers bringing their own data. WHAT SUCCESS WILL LOOK LIKE (6-12 MONTHS) - A private cloud deployment is a ~1-day turnkey operation. Playbooks and templated Terraform make standing up Elicit in a customer's cloud routine, which opens up 8-figure enterprise deals. - Our observability signal:noise ratio improves 10-fold. Health monitors cover every endpoint and job, and an alert firing means something needs attention. - Disaster recovery is practiced. We run database restoration drills and provider-outage dry runs on a schedule, with post-mortems that make the whole team better at diagnosis. - Our SLAs are backed by engineering rigor. We follow through on SOC 2, NIST AI framework, and EU Cyber Resilience commitments, and enterprise security reviews go faster because of it. - Inference is faster and cheaper. You've found and executed opportunities like shifting load between providers to cut p95 latency and cost at the same time. WHAT WE'RE LOOKING FOR - 5+ years of hands-on infrastructure/SRE/platform engineering experience. - An AI-native way of working. Agentic coding tools (Claude Code, Cursor, Devin, etc.) are how we build at Elicit, and infrastructure is no exception: agents help us write IaC and investigate incidents. You should be an enthusiastic practitioner who uses AI to multiply your impact, and excited to find new places agents can safely take on infrastructure work. Bonus: you've written about, spoken about, or built projects demonstrating this. - Solid Terraform experience. this is our primary infrastructure-as-code layer and the most important technical requirement. - Strong Kubernetes expertise. You've operated production clusters, not just deployed to them. Comfortable with EKS, networking, autoscaling (Karpenter), and debugging cluster-level issues. - AWS experience (primary), with GCP familiarity a plus. - GitOps and CI/CD fluency. Argo CD, GitHub Actions, or equivalent. You understand deployment automation, rollback strategies, and change management. - SRE mindset. You've built or significantly improved observability stacks (DataDog or equivalent), incident response processes, and on-call practices. - Security and compliance awareness. Experience with SOC 2 or similar frameworks, SIEM tooling, and translating compliance requirements into engineering practice. - Ability to write software. You can contribute to our backend codebases where infrastructure meets application logic. AM I A GOOD FIT? Strong applicants will find it easy to answer these questions: 1. Can you describe a time you designed and executed a multi-tenant or single-tenant deployment architecture for enterprise customers? 2. How have you approached disaster recovery planning and testing at a previous company? 3. Walk me through how you'd evaluate whether to build vs. buy for a new infrastructure component at a ~30-person startup. 4. Have you owned compliance follow-through (not just policy writing) for a framework like SOC 2? WHO WILL I WORK WITH? - James (Head of Engineering): set up the original infrastructure and will be your closest partner. You'll own execution, with James as sounding board and advocate. - Panda: the engineer who has been covering infrastructure part-time, with deep context on our cluster bootstrapping, Cloudflare setup, and inference providers. - Product: PMs covering the core product, ML, and evals. They carry the customer side of enterprise deployments, so you'll work together to turn requirements like data residency, compliance commitments, and SLAs into architecture, and to weigh the cost and latency tradeoffs behind product decisions. Eval infrastructure is a shared surface with Ben, from CI integration to inference capacity. - The whole engineering team: we're ~30 people company-wide, so you'll work directly with the engineers whose developer experience you're improving, and pair with them where infrastructure meets application code. - Andreas and Jungwon (cofounders): you'll meet both during the interview process, and infrastructure decisions with strategic weight (enterprise deployments, compliance posture) get their direct attention. ON-CALL & INCIDENT EXPECTATIONS We don't have a formal on-call rotation yet. Incidents today are handled by the engineers closest to the affected system. Part of this role is building the incident response practice we should have: sensible alerting, SLA tracking, structured post-mortems, and eventually a rotation designed so it doesn't burn anyone out. You'd design the on-call setup you'll then live with. WHY JOIN US? The work matters. Our mission https://blog.elicit.com/mission/ is to radically improve reasoning for high-stakes decisions. Over 2 million people use Elicit, including pharma teams making R&D decisions worth tens of millions of dollars, and the reliability of our platform is part of what makes those decisions sound. - Infrastructure work is close to the business. Single-tenant deployments open enterprise deals, and inference routing choices show up directly in our costs and latency. You'll see the effect of your work in the company's trajectory. - Built for the long term. We're a Public Benefit Corporation that spun out of a non-profit AI research lab. Long-term impact and AI safety are part of the corporate charter. - High agency, low bureaucracy. ~30 curious, slightly weird people who write things down and trust each other to run with a vague brief. - Serious investment in your growth. $1,000 per quarter for every person to explore AI tools, courses, and events, plus quarterly in-person team retreats. LOCATION AND TRAVEL We have a great office in Oakland, CA, and we'd love to see you there if you're local. That said, we're just as happy for you to work remotely. We do get the whole team together for a quarterly retreat somewhere fun, because in-person time matters to us. BENEFITS AND PERKS In addition to working on important problems as part of a productive and positive team, we also offer great benefits (with some variation based on location): - Flexible work environment: work from our office in Oakland or remotely with time zone overlap (between GMT and GMT-8), as long as you’re comfortable traveling for quarterly in-person offsites. - Fully covered health, dental, vision, and life insurance for you, generous coverage for the rest of your family (FSA/HSA, too). - Flexible vacation policy, with a minimum recommendation of 20 days / year and plenty of company holidays. - Every Elician receives a $200 monthly wellbeing stipend to spend on whatever supports your health and wellbeing. - 401K with a 6% employer match. - A new Mac + $1,000 budget to set up your workstation or home office in your first year, then $500 every year thereafter. - $1,000 quarterly AI Experimentation & Learning budget, so you can freely experiment with new AI tools to incorporate into your workflow, take courses, purchase educational resources, or attend AI-focused conferences and events. - A team administrative assistant who can help you with personal and work tasks. - You can find more reasons to work with us in this thread https://twitter.com/stuhlmueller/status/1694059800408269091! COMPENSATION For all roles at Elicit, we use a data-backed compensation framework to keep salaries market-competitive, equitable, and simple to understand. For this role, we target starting ranges of: - Senior (L4): $185-260k + equity - Expert (L5): $250-280k + equity - Principal (L6): >$260 + significant equity We're optimizing for a hire who can contribute at a L4/senior-level or above. We offer above-market equity for all roles at Elicit, as well as employee-friendly equity terms.
Applied AI Researcher, AI Systems
ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. WHAT WE ARE LOOKING FOR At Distyl we’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used. Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org. KEY RESPONSIBILITIES - The AI Systems team focuses on designing compound, end-to-end architectures that orchestrate perception, reasoning, planning, and execution. Researchers integrate diverse components (LLMs, retrievers, evaluators, memory systems, and execution agents) into robust, scalable systems that perform reliably across dynamic enterprise workflows. - Researchers in AI Systems investigate the governing principles behind complex system interactions. They study coordination, information flow, and emergent behavior across multiple agents and models. Their work identifies the underlying mechanics of robustness, composability, and alignment, in effect establishing the design language for how intelligent systems should be built. WHO YOU ARE - Experience Building with Models, Not Just Building Models: We develop intelligent systems using models rather than training or fine-tuning them. Ideal candidates have expertise in compound AI systems, agentic collaboration, and associated techniques (ensembling, ReAct, graph-of-thoughts, etc.). - Proven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done. - Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow. - Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI. - Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize. WHAT WE OFFER - The base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible time off - Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources - Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot - Complimentary in-office lunches and snacks provided - Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems - Ownership of high-impact projects across top enterprises - A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office. #LI-Hybrid We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
Join Our Talent Network - Senior/Staff AI Algorith...
About Dexterity At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring, problem-solving jobs that humans do best by enabling robots to handle repetitive and physically difficult work. We’re starting with warehouse automation, where the need for smarter, more resilient supply chains impacts millions of lives and businesses worldwide. Dexterity's full-stack robotics systems pick, move, pack, and collaborate with human-like skill, awareness, and learning capabilities. Our systems are software-driven and hardware-agnostic and have already picked 100+ million goods in production. And did we mention we’re customer-obsessed? Every decision, large and small, is driven by one question – how can we empower our customers with robots to do more than they thought was possible? Dexterity is one of the fastest-growing companies in robotics, backed by world-class investors such as Kleiner Perkins, Lightspeed Venture Partners, and Obvious Ventures. We’re a diverse and multidisciplinary team with a culture built on passion, trust, and dedication. Come join Dexterity and help make intelligent robots a reality! About the Role We’re looking for an Senior/Staff AI Algorithms Engineer with deep foundations in machine learning, reinforcement learning, and optimization—and a strong drive to apply those skills to novel, high-impact problems in robotics. You will leverage techniques from machine learning, reinforcement learning, search, and optimization to solve hard sequential decision problems that require reasoning about the physical world and its dynamics. You will also stay abreast of the latest progress in reinforcement learning, task and motion planning, and other related fields in order to further enhance Dexterity’s technology foundations in Physical AI You’ll be part of a team working across simulation, real robots, and multimodal sensor streams, applying first-principles thinking to unlock product capabilities where off-the-shelf ML solutions fall short. If you have strong research instincts but are excited to build things that are used in the real world, this role offers the chance to turn deep technical ideas into systems deployed at scale. What You'll Do Design and prototype novel algorithms at the intersection of learning, prediction, and planning, with a focus on solving real product challenges Apply reinforcement learning, geometric reasoning, or optimization-based methods to tackle long-horizon manipulation, sensor fusion, or decision-making under uncertainty Translate open-ended problems into clear technical approaches, balancing modeling intuition with real-world constraints like latency, reliability, and partial observability Build and test your algorithms across simulation and real-robot environmentsCollaborate closely with product leads, software engineers, and roboticist to bring ideas into fruition Contribute to internal knowledge, tooling, and experimentation pipelines that level up the entire team What We’re Looking For PhD or equivalent experience in machine learning, robotics, optimization, applied math, or a related field Strong mathematical foundation in areas such as probability, statistics, optimization, reinforcement learning, imitation learning, and foundation models Ability to turn theoretical insights into practical, testable code using Python and PyTorch (or similar frameworks) Curiosity, initiative, and a bias toward building and debugging in real systems Clear communication skills and an ability to collaborate across engineering and research boundaries Nice to Have Experience with physics simulators, control stacks, or physical sensing modalities (RGBD, force-torque, etc.) Prior work on real-world ML deployments (e.g., autonomous vehicles, logistics, hardware-integrated ML) Contributions to open-source ML, RL, or robotics libraries Previous startup experience Why this Role You’ll work on hard, novel problems that demand first-principles thinking—not just tuning models Your work will run on physical systems with real constraints, feedback, and real world impact You’ll be expected to and supported in owning high-impact projects from early on You’ll have a chance to help shape how learning, prediction, and planning come together in next-generation robotics
Join Our Talent Network - Senior Robotics Manipula...
About Dexterity: At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring, problem-solving jobs that humans do best by enabling robots to handle repetitive and physically difficult work. We’re starting with warehouse automation, where the need for smarter, more resilient supply chains impacts millions of lives and businesses around the world. Dexterity's full-stack robotics systems pick, move, pack, and collaborate with human-like skill, awareness, and learning capabilities. Our systems are software-driven, hardware-agnostic, and have already picked over 15 million goods in production. And did we mention we’re customer-obsessed? Every decision, large and small, is driven by one question – how can we empower our customers with robots to do more than they thought was possible? Dexterity is one of the fastest growing companies in robotics, backed by world-class investors such as Kleiner Perkins, Lightspeed Venture Partners, and Obvious Ventures. We’re a diverse and multidisciplinary team with a culture built on passion, trust, and dedication. Come join Dexterity and help make intelligent robots a reality! As a Senior Robotics Manipulation Engineer, you will be working on a myriad of challenges related to manipulation, control, simulation and learning. You will bring a data driven approach to learned robot controls. You will also stay abreast of the latest progress in reinforcement learning, motion planning and controls, and other related fields in order to further develop Dexterity’s technology foundations in physical AI. Dexterity’s robotic solutions integrate data from a multitude of sensors, including RGB cameras, depth sensors, force-torque sensors, encoders, system telemetry and human input. To better inform the planning and execution system, you may work on sensor fusion and state estimation techniques to leverage this multimodal sensory data. You will work closely with the data platform, simulation, and robot operations teams to collect training data to improve your models. In addition to core manipulation and controls, you will be responsible for building high quality, maintainable, and performant software. Ideally, you will possess strong software system and interface design skills. Day to Day Activities: Train models for robotic manipulation, force control, servoing etc. Convert heuristics based control to learned models. Develop the right state space representation for our Robotics Systems. Collaborate with roboticist, machine learning engineers, mechanical engineers, and product managers to find optimal system solutions. Implement, test, and maintain high quality software. Lead efforts to improve the rigor and performance of models within Dexterity. Required Skills: BS/MS/PhD in Computer Science or a related discipline. 5+ years of relevant Industry or Research experience. Strong Python programming skills. Knowledge of Modern C++ and Linux. Experience with multiple of the following: Artificial Intelligence (imitation learning, reinforcement learning, deep learning, LLMs) Distributed ML Training Platforms (Ray or other) Task and Motion Planning Simulation Nice to haves: Experience with Git and modern CI pipelines. Experience with Docker and Kubernetes Previous startup experience
Senior Product Marketing Manager, Voice Agent
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. Voice agents are becoming standard infrastructure for customer-facing businesses, and the platform teams build on decides whether they ship something production-grade or something that stalls in a demo. Deepgram Voice Agent is a single, unified API that combines speech-to-text, LLM orchestration, and text-to-speech in real time: the full voice stack, owned end to end. We're looking for a Senior PMM to own our go-to-market motion and make Deepgram the default teams reach for when they move from prototype to production. This is a market ownership role. You'll define how Deepgram shows up in a crowded, fast-moving category, build the narrative for where an owned, end-to-end runtime fits across how teams build voice agents, drive adoption from developer trial through enterprise deployment, and own product launches as they come. You'll work across Product, Sales, Developer Relations, and Demand Gen to keep the voice agent story consistent, compelling, and closing deals. We're an AI-native team. We expect AI to be woven into how you work, not something you reach for occasionally. WHAT YOU'LL DO - Own the voice agent category narrative. Define what a production-grade voice agent platform is in a way that plays to Deepgram's strengths: one owned, end-to-end stack with sub-300ms latency, barge-in, and turn-taking. - Build and execute GTM strategy across developer adoption, pipeline influence, and account expansion. Voice agents are where STT, TTS, and LLM orchestration come together; own the full-stack story while knowing how the pieces show up in broader deals. - Lead product launches for Voice Agent releases: new conversational capabilities, latency and quality advances, BYO model support, deployment and compliance options. Clear messaging, sharp launch plans, tight cross-functional execution. - Own positioning across the build spectrum. Understand the different approaches teams take to building voice agents, from DIY frameworks to managed platforms and enterprise suites, and build the battlecards, objection-handling guides, and build-vs-buy narratives that show why the unified-API approach wins for production. Many players here are partners who embed Deepgram as their speech layer. - Enable sales and build proof points. Collateral, customer stories, benchmarks, and TCO narratives that win voice agent deals and stand up to technical and economic scrutiny. - Collaborate with Product on market and competitive intelligence: what voice agent builders need, what the market is shipping, where it's going. - Drive developer-facing content and awareness with Developer Relations: tutorials, documentation messaging, reference architectures, use case content, and SEO tied to how voice agent builders actually search. - Build AI-assisted PMM workflows. Use AI to accelerate research, competitive synthesis, and content production. Build repeatable systems, not one-off prompts. You set the strategy; AI handles the first drafts. YOU'LL LOVE THIS ROLE IF YOU - Are energized by owning a market, not just supporting a product. You want to shape how buyers think about the problem. - Understand the voice agent stack well enough to tell a coherent story about why an owned, end-to-end platform beats a stitched-together one, and where the build-vs-buy line falls for different buyers. - Move fluidly between a developer audience and a business buyer without losing either one. - Are comfortable marketing a product with both a technical architecture story and an experiential one, where one buyer is reading API docs and another is judging whether the agent sounds and responds like something they'd put in front of customers. - Default to AI-first: you use AI continuously, have good judgment about when it's wrong, and think in systems rather than one-off prompts. IT'S IMPORTANT TO US THAT YOU HAVE - 5+ years of product marketing experience, including at least 2 years on infrastructure, API, or developer-facing products. - Strong messaging skills: you can build a positioning architecture from scratch and know the difference between a message that's technically accurate and one that actually moves people. - A high bar for quality: you notice when copy is off, when a layout doesn't work, when creative doesn't match the brand, and you can give useful feedback on all of it. - Working knowledge of the AI landscape: frontier models, major LLM providers, how the ecosystem fits together. You need to talk about this credibly with technical buyers. - Technical depth: you can engage with engineering and product teams, read API docs, and translate product-level details into market-facing narratives without oversimplifying. - Fluency in both product-led and sales-led growth motions, and how they interact. - Demonstrated AI fluency: concrete examples of AI-assisted workflows you've built, iterated on, and measured, with specific outcomes to back it up. IT WOULD BE GREAT IF YOU HAD - Experience in the voice AI space and familiarity with how STT, TTS, and LLMs come together in a production voice agent stack, and with the range of ways teams build voice agents, from DIY frameworks to managed platforms. - Hands-on experience with AI-native tools across the stack: agentic coding (Claude Code, Codex) and collaborative work tools (Cowork, etc.). - Experience with technical proof points, model benchmarks, or evaluation frameworks. In voice agents, buying decisions often come down to a live conversation that either feels natural or doesn't. - Comfort operating where the playbook doesn't fully exist yet and you're building it as you go. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
ML Ops Infrastructure Engineer
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. THE OPPORTUNITY Getting a model from a research notebook to a production API serving millions of requests is one of the hardest problems in AI. As an ML Ops Infrastructure Engineer at Deepgram, you will own the critical bridge between research and production -- building the pipelines, deployment systems, and testing infrastructure that take models from experimental to battle-tested at scale. Your work ensures that every model improvement our research team makes can be safely, quickly, and reliably delivered to the customers who depend on Deepgram's APIs for real-time voice AI. WHAT YOU'LL DO - Design and build CI/CD pipelines specifically tailored for ML model development, validation, and deployment - Architect and maintain model deployment pipelines that move models from research environments through staging to production with confidence - Build A/B testing infrastructure that enables controlled rollouts of new models and measures real-world performance impact - Implement comprehensive monitoring for model performance in production -- accuracy metrics, latency, drift detection, and regression alerts - Develop automated retraining pipelines that trigger on data changes, performance degradation, or scheduled cadences - Create and maintain build and test environments that mirror production, giving researchers high-fidelity feedback before deployment - Establish model versioning, artifact management, and rollback capabilities to ensure safe and reproducible deployments - Collaborate with research engineers to define and enforce model quality gates before production promotion - Build observability dashboards that give the team real-time insight into model health across all environments - Optimize model serving infrastructure for latency, throughput, and cost efficiency YOU'LL LOVE THIS ROLE IF YOU - Are excited by the challenge of operationalizing cutting-edge AI models at production scale - Believe that great infrastructure is what turns research breakthroughs into customer value - Enjoy designing systems that are automated, reliable, and self-healing - Want to work on problems where minutes of latency reduction or percentage points of accuracy matter enormously - Like collaborating across research and engineering teams to make the whole organization faster - Are motivated by building the deployment and testing systems that back a platform serving over 200,000 developers IT'S IMPORTANT TO US THAT YOU HAVE - 4+ years of experience in MLOps, DevOps, or infrastructure engineering with a focus on ML systems - Strong proficiency in Python and experience building automation and tooling for ML workflows - Deep experience with CI/CD systems and building pipelines for software and model delivery - Hands-on experience with Docker and Kubernetes for containerized workload management - Practical experience deploying and serving ML models in production environments - Familiarity with model evaluation, validation, and quality assurance processes - Understanding of monitoring and observability principles as applied to ML systems - Strong problem-solving skills and a bias toward automation over manual processes IT WOULD BE GREAT IF YOU HAD - Experience with model serving frameworks such as NVIDIA Triton Inference Server, TensorRT, or ONNX Runtime - Background in speech, audio, or real-time media ML systems - Experience with Infrastructure as Code tools such as Terraform or Pulumi - Hands-on experience with monitoring and observability stacks (Prometheus, Grafana, Datadog, or similar) - Familiarity with GPU-accelerated inference optimization and profiling - Experience with feature stores, data versioning, or ML metadata management - Knowledge of canary deployment strategies and progressive delivery for ML models Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Applied ML Engineer - Edge Devices
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. ABOUT THE ROLE Deepgram's speech models are among the fastest and most accurate in the world, and today we run them at scale on NVIDIA GPUs. Our customers increasingly need those same models on hardware we don't control: non-NVIDIA accelerators, edge servers, and embedded platforms with their own inference runtimes, operator sets, and constraints. Getting Deepgram models onto those platforms, with as few changes to the model as possible and no changes to the hardware paradigm, is the job. As an Applied ML Engineer on the Partner Platform Engineering team, you sit one layer above the metal. You take a Deepgram model as it exists today and adapt it to run correctly and efficiently within a target platform's existing kernel and runtime paradigm: swapping or reshaping operators, adjusting architecture parameters, choosing quantization and precision schemes, and validating accuracy and latency on the real device. Where a standard kernel isn't enough, you work with our Embedded AI Engineers, who write the custom kernels, and fit the model to what they build. You also own the deployment process that gets those adapted models onto edge targets repeatably. This is not a research role and not a cloud-serving role. It is applied ML for edge deployment. It is a great fit for a senior engineer who has already shipped models to non-GPU or edge hardware and wants to do it across many platforms, or a staff-level engineer who wants to define how Deepgram ports speech models to new hardware. We'll set the level to your experience. WHAT YOU'LL DO - Port Deepgram speech models to non-NVIDIA and edge platforms, adapting model structure and parameters so they run within the target's existing operator set, runtime, and kernels with minimal modification. - Own serving-side model decisions for edge targets: quantization and precision choices, operator substitution, graph rewrites, and architecture tweaks that fit a model to a device's constraints while holding accuracy and latency. - Validate every port on real hardware: build accuracy, latency, throughput, and memory benchmarks per platform, and catch regressions before a customer does. - Build the deployment path for edge targets: model packaging, conversion pipelines, versioning, and automated delivery so shipping a model to a new device is repeatable rather than bespoke. - Work with Embedded AI Engineers when a standard kernel isn't enough: specify what the model needs, then adapt the model to use the custom kernel they deliver. - Partner with platform and silicon vendors on their runtimes and toolchains, and turn their expected model format and operator conventions into a working Deepgram deployment. - Feed edge constraints back to Research and Impeller so future models are easier to port, without taking on research or core productionization work yourself. - As the team grows, take on adjacent production concerns at the edge: automated deployment, model security and integrity on customer hardware, and fleet-level observability. YOU'LL LOVE THIS ROLE IF YOU - Have already fought to get a model running on hardware that wasn't built for it, and want to do that across many platforms. - Prefer changing the model to fit the hardware over changing the hardware to fit the model, and know when each is the right call. - Care about the numbers on the device, not the numbers in the notebook. - Like being the bridge between the team writing kernels and the team training models. - Want to ship to customers, not publish. IT'S IMPORTANT TO US THAT YOU HAVE - Hands-on experience deploying ML models to edge or non-NVIDIA hardware in production. This is required. Cloud-only or GPU-only serving experience does not qualify on its own. - Working knowledge of quantization and precision tradeoffs (INT8, FP16, mixed precision, calibration) and how they affect accuracy and latency on real targets. - Experience with at least one edge or vendor inference runtime and its conversion toolchain (for example ONNX Runtime, TFLite, ExecuTorch, OpenVINO, Qualcomm AI Engine, or a vendor NPU SDK). - Ability to modify a model to fit a platform: reading and rewriting model graphs, swapping unsupported operators, and adjusting architecture parameters without breaking accuracy. - Strong Python and PyTorch, and production-quality engineering habits: tests, reproducibility, and benchmarks that others can rerun. - Comfort building automation around model conversion and deployment. - A builder mindset and clear communication: you can scope a port on an unfamiliar platform and drive it to a measured result. IT WOULD BE GREAT IF YOU HAD - Experience with speech, audio, or streaming/real-time models specifically. - Exposure to writing or reading low-level kernels (CUDA, Metal, NEON, or vendor DSP code), enough to collaborate closely with embedded engineers. - Experience with model security or integrity on deployed devices: signing, encrypted model storage, safe updates. - Familiarity with several accelerator families (Qualcomm, Apple, ARM, Intel, AMD, or custom NPUs) and their quirks. - A track record of building internal tooling that made porting or deploying models measurably faster. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Staff Software Engineer, Voice Agent
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team The Voice Agent team builds the real-time systems that allow Decagon agents to carry natural conversations across our omnichannels (phone, web, mobile, etc). We work across speech understanding, audio streaming, synthesis quality, and the voice specific execution logic that enables timing, pacing, and responsive dialogue. Our systems must remain accurate, responsive, and stable at scale. Voice is one of the most technically challenging surfaces in conversational AI, and our small team owns this entire capability end-to-end. About the Role As a Staff Software Engineer focused on Voice Agent, you will lead the architecture and evolution of Decagon’s voice platform. You will drive multi-quarter projects that improve timing, responsiveness, audio quality, and reliability across millions of interactions. You will collaborate with Research to integrate the next generation of speech models, with Infra to push the boundaries of latency and performance, and with Product to bring new voice capabilities to customers. You will help set engineering standards for voice, mentor senior engineers, and raise the technical bar for one of Decagon’s most important surfaces. In this role, you will - Own the architecture of Decagon’s real-time voice runtime and shape its long-term roadmap - Lead initiatives that improve speech understanding, synthesis quality, and conversational timing - Define reliability, testing, and observability standards for live voice interactions - Build frameworks that make voice systems easy to debug, measure, and iterate on - Mentor senior engineers and help expand the technical culture of the Voice group Your background looks something like this - 8+ years of engineering experience with significant technical leadership - Expertise in real-time systems, streaming pipelines, or audio-based applications - Ability to define architectural direction and lead cross-functional projects - Strong debugging skills across audio, networking, and model-driven systems - Experience mentoring engineers and influencing engineering standards Even better if you have - Experience with speech recognition or synthesis systems - Experience with VAD, streaming protocols, or other real-time audio systems - Experience designing or maintaining LLM-driven applications - Experience optimizing performance for low-latency use cases Compensation $200K – $400K + Offers Equity This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact. In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States. Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Senior Software Engineer, AI Platform
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. ABOUT THE TEAM The AI Platform team builds the foundational systems that enable every engineer at Decagon to build with AI. Our users are both engineers and coding agents. We build the execution environments, agent harnesses, evaluation systems, developer tools, and shared abstractions they use to plan, write, test, review, and ship production software. We sit within Infrastructure and work closely with product, ML, data, and security teams. Our goal is to turn rapidly evolving agent capabilities into reliable, secure platforms that materially change how software gets built at Decagon. ABOUT THE ROLE We’re looking for an experienced software engineer to help build Decagon’s AI-native developer platform. You’ll work at the intersection of distributed systems, developer tooling, and applied AI. You will experiment with new agentic workflows, identify where they create real leverage, and turn the best ideas into dependable systems used across the engineering organization. This is a highly product-oriented platform role. You’ll work directly with engineers to understand how they build software, find high-value opportunities for automation, and own solutions from architecture and implementation through rollout, adoption, and production operation. A few areas you may work on: - Agent execution: Build harnesses, orchestration systems, and isolated environments where coding agents can safely execute long-running tasks. - Tools and context: Give agents secure, observable access to codebases, tests, documentation, internal systems, and the tools needed to complete real engineering work. - Agentic development workflows: Apply AI across planning, technical design, implementation, testing, code review, and production operations. - Evaluation and validation: Build systems that test and review human- and agent-generated changes, catch regressions earlier, and improve confidence in autonomous development. - Agent-native developer infrastructure: Design CI/CD, local development, APIs, CLIs, and platform tooling that can be operated directly by both engineers and agents. - Internal builder platforms: Create reusable frameworks that let teams quickly build their own internal tools, dashboards, automations, and agents. WHAT YOU'LL DO - Design, build, and operate the core platform behind agent-driven software development at Decagon. - Lead ambitious platform projects from an ambiguous problem through technical design, implementation, rollout, and long-term evolution. - Turn successful experiments into secure, reusable abstractions that engineering teams can adopt without becoming experts in the underlying infrastructure. - Partner closely with engineers across the company to understand bottlenecks, prototype solutions, and drive adoption. - Improve the speed and quality of software development through better agent tooling, testing, review, and automation. - Own the reliability, observability, security, performance, and cost of the systems you build. - Help define how Decagon engineers—and increasingly autonomous agents—build and operate production software. YOU MIGHT BE A GREAT FIT IF YOU - Have 4+ years of experience building production software, particularly in backend, infrastructure, platform, or developer tooling. - Are a strong programmer in Python, TypeScript, or another systems-oriented language. - Have designed and operated APIs, services, or platforms that other engineers depend on. - Understand distributed systems, cloud infrastructure, containers, and production reliability. - Have taken technically complex projects from ambiguous problem statements to widely adopted production systems. - Care deeply about developer experience and know how to turn complicated infrastructure into simple, useful abstractions. - Move quickly while maintaining a high bar for correctness, security, and operational quality. - Communicate clearly and enjoy working directly with the engineers who use what you build. EVEN BETTER IF YOU HAVE - Experience building coding agents, tool-use systems, agent harnesses, or sandboxed execution environments. - Experience with CI/CD systems, build infrastructure, monorepos, or large-scale test automation. - Built evaluation, testing, or review systems for AI-generated code. - Experience with Kubernetes, infrastructure as code, secrets management, or identity and access systems. - Built an internal developer platform or shared tooling that achieved meaningful adoption across an engineering organization. - Applied AI to materially improve engineering velocity, reliability, or software quality. COMPENSATION $200K – $400K + Offers Equity This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact. In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States. Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Agent Deployment Engineer - Spanish Speaking
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Over the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require hands-on execution, rigorous iteration, and deep technical delivery to reach enterprise-grade performance. We’re creating an Agent Deployment Engineering Org: a specialized technical delivery team responsible for end-to-end execution of AI agent builds. Agent Deployment Engineers own the hands-on work required to deliver best-in-class agents—writing and configuring key components, validating integrations, and ensuring agents perform reliably at scale. This team brings greater specialization and focus to build quality. Agent Deployment Engineers are technical and customer-facing: you’ll interface with senior technical stakeholders on the customer side while also going deep on agent configuration and build execution. About the Role As an Agent Deployment Engineer, you will be responsible for end-to-end execution of AI agent builds for strategic customers. This is a highly technical delivery role where you will own the implementation work required to launch and scale enterprise-quality agents—partnering with customers and internal teams to define success, translate requirements into build plans, and deliver agents that meaningfully impact the customer’s business. You’ll work closely with Agent PMs, Agent Success, Engineering, and GTM teams to create tight feedback loops: executing builds, surfacing gaps, and influencing the evolution of Decagon’s agent-building platform based on real customer needs. This role is ideal for someone who thrives in fast-moving environments, enjoys shipping customer-facing technical work, and can balance hands-on execution with structured thinking. In this role, you will - Own end-to-end architecture and execution of AI agent builds for enterprise customers, from systems design and initial scoping through implementation, evaluation, and production deployment. - Design and engineer the core agentic logic governing agent behavior, applying engineering principles to optimize quality, reliability, and correctness across non-deterministic model outputs. - Engineer and validate layered guardrails and supervisory controls to ensure safe, compliant, and predictable agent performance across real-world scenarios. - Architect, build, and test integrations with customer systems (e.g., data pipelines, CRMs, ticketing systems), including building the tools, APIs, and workflows needed for reliable deployments at scale. - Interface with senior technical stakeholders at customers to define success criteria and system requirements, and drive technical delivery against timelines. - Diagnose, debug, and resolve both probabilistic and technical failures through root-cause analysis of execution traces, error logs, and model behavior. - Design evaluation and regression-testing frameworks to validate agent behavior against ground truth and guard against performance drift. - Translate customer needs into clear internal documentation and run tight feedback loops with Engineering to drive platform improvements. - Partner closely with APMs, Engineering, Design, and Go-To-Market teams to deliver consistent, repeatable, best-in-class agent builds. Your background looks something like this - Have 5+ years of relevant experience in a technical customer-facing role (e.g., solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, technical product/PM, or similar). - Native or business-level fluency in both written and spoken English and Spanish is required. - Strong technical foundation: comfortable writing code, working with APIs, and building/validating integrations end-to-end. Experience delivering production-grade customer solutions that require structured execution, testing/validation, and iteration. - Ability to communicate clearly with senior technical stakeholders, translate requirements into implementation plans, and drive delivery. - Comfort working in fast-moving, ambiguous environments where you shape solutions as much as you implement them. Even better if you have - Experience building with or around LLMs / AI agents (prompting, evaluation, guardrails, tooling, workflow design, etc.). - Experience with enterprise SaaS integrations (e.g., ticketing systems, CRM, data pipelines) and associated security/compliance considerations. - A Computer Science, Engineering, or Math degree, or equivalent technical experience. - Strong product instinct: ability to write crisp PRDs, define success metrics, and contribute customer insight back into product roadmap. Compensation $175K – $230K • Offers Equity Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Agent Deployment Engineer - German Speaking
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Over the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require hands-on execution, rigorous iteration, and deep technical delivery to reach enterprise-grade performance. We’re creating an Agent Deployment Engineering Org: a specialized technical delivery team responsible for end-to-end execution of AI agent builds. Agent Deployment Engineers own the hands-on work required to deliver best-in-class agents—writing and configuring key components, validating integrations, and ensuring agents perform reliably at scale. This team brings greater specialization and focus to build quality. Agent Deployment Engineers are technical and customer-facing: you’ll interface with senior technical stakeholders on the customer side while also going deep on agent configuration and build execution. About the Role As an Agent Deployment Engineer, you will be responsible for end-to-end execution of AI agent builds for strategic customers. This is a highly technical delivery role where you will own the implementation work required to launch and scale enterprise-quality agents—partnering with customers and internal teams to define success, translate requirements into build plans, and deliver agents that meaningfully impact the customer’s business. You’ll work closely with Agent PMs, Agent Success, Engineering, and GTM teams to create tight feedback loops: executing builds, surfacing gaps, and influencing the evolution of Decagon’s agent-building platform based on real customer needs. This role is ideal for someone who thrives in fast-moving environments, enjoys shipping customer-facing technical work, and can balance hands-on execution with structured thinking. In this role, you will - Own end-to-end architecture and execution of AI agent builds for enterprise customers, from systems design and initial scoping through implementation, evaluation, and production deployment. - Design and engineer the core agentic logic governing agent behavior, applying engineering principles to optimize quality, reliability, and correctness across non-deterministic model outputs. - Engineer and validate layered guardrails and supervisory controls to ensure safe, compliant, and predictable agent performance across real-world scenarios. - Architect, build, and test integrations with customer systems (e.g., data pipelines, CRMs, ticketing systems), including building the tools, APIs, and workflows needed for reliable deployments at scale. - Interface with senior technical stakeholders at customers to define success criteria and system requirements, and drive technical delivery against timelines. - Diagnose, debug, and resolve both probabilistic and technical failures through root-cause analysis of execution traces, error logs, and model behavior. - Design evaluation and regression-testing frameworks to validate agent behavior against ground truth and guard against performance drift. - Translate customer needs into clear internal documentation and run tight feedback loops with Engineering to drive platform improvements. - Partner closely with APMs, Engineering, Design, and Go-To-Market teams to deliver consistent, repeatable, best-in-class agent builds. Your background looks something like this - Have 5+ years of relevant experience in a technical customer-facing role (e.g., solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, technical product/PM, or similar). - Native or business-level fluency in both written and spoken English and German is required. - Strong technical foundation: comfortable writing code, working with APIs, and building/validating integrations end-to-end. Experience delivering production-grade customer solutions that require structured execution, testing/validation, and iteration. - Ability to communicate clearly with senior technical stakeholders, translate requirements into implementation plans, and drive delivery. - Comfort working in fast-moving, ambiguous environments where you shape solutions as much as you implement them. Even better if you have - Experience building with or around LLMs / AI agents (prompting, evaluation, guardrails, tooling, workflow design, etc.). - Experience with enterprise SaaS integrations (e.g., ticketing systems, CRM, data pipelines) and associated security/compliance considerations. - A Computer Science, Engineering, or Math degree, or equivalent technical experience. - Strong product instinct: ability to write crisp PRDs, define success metrics, and contribute customer insight back into product roadmap. Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Agent Deployment Engineer - French Speaking
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Over the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require hands-on execution, rigorous iteration, and deep technical delivery to reach enterprise-grade performance. We’re creating an Agent Deployment Engineering Org: a specialized technical delivery team responsible for end-to-end execution of AI agent builds. Agent Deployment Engineers own the hands-on work required to deliver best-in-class agents—writing and configuring key components, validating integrations, and ensuring agents perform reliably at scale. This team brings greater specialization and focus to build quality. Agent Deployment Engineers are technical and customer-facing: you’ll interface with senior technical stakeholders on the customer side while also going deep on agent configuration and build execution. About the Role As an Agent Deployment Engineer, you will be responsible for end-to-end execution of AI agent builds for strategic customers. This is a highly technical delivery role where you will own the implementation work required to launch and scale enterprise-quality agents—partnering with customers and internal teams to define success, translate requirements into build plans, and deliver agents that meaningfully impact the customer’s business. You’ll work closely with Agent PMs, Agent Success, Engineering, and GTM teams to create tight feedback loops: executing builds, surfacing gaps, and influencing the evolution of Decagon’s agent-building platform based on real customer needs. This role is ideal for someone who thrives in fast-moving environments, enjoys shipping customer-facing technical work, and can balance hands-on execution with structured thinking. In this role, you will - Own end-to-end architecture and execution of AI agent builds for enterprise customers, from systems design and initial scoping through implementation, evaluation, and production deployment. - Design and engineer the core agentic logic governing agent behavior, applying engineering principles to optimize quality, reliability, and correctness across non-deterministic model outputs. - Engineer and validate layered guardrails and supervisory controls to ensure safe, compliant, and predictable agent performance across real-world scenarios. - Architect, build, and test integrations with customer systems (e.g., data pipelines, CRMs, ticketing systems), including building the tools, APIs, and workflows needed for reliable deployments at scale. - Interface with senior technical stakeholders at customers to define success criteria and system requirements, and drive technical delivery against timelines. - Diagnose, debug, and resolve both probabilistic and technical failures through root-cause analysis of execution traces, error logs, and model behavior. - Design evaluation and regression-testing frameworks to validate agent behavior against ground truth and guard against performance drift. - Translate customer needs into clear internal documentation and run tight feedback loops with Engineering to drive platform improvements. - Partner closely with APMs, Engineering, Design, and Go-To-Market teams to deliver consistent, repeatable, best-in-class agent builds. Your background looks something like this - Have 5+ years of relevant experience in a technical customer-facing role (e.g., solutions engineering, forward-deployed engineering, technical consulting, implementation engineering, technical product/PM, or similar). - Native or business-level fluency in both written and spoken English and French is required. - Strong technical foundation: comfortable writing code, working with APIs, and building/validating integrations end-to-end. Experience delivering production-grade customer solutions that require structured execution, testing/validation, and iteration. - Ability to communicate clearly with senior technical stakeholders, translate requirements into implementation plans, and drive delivery. - Comfort working in fast-moving, ambiguous environments where you shape solutions as much as you implement them. Even better if you have - Experience building with or around LLMs / AI agents (prompting, evaluation, guardrails, tooling, workflow design, etc.). - Experience with enterprise SaaS integrations (e.g., ticketing systems, CRM, data pipelines) and associated security/compliance considerations. - A Computer Science, Engineering, or Math degree, or equivalent technical experience. - Strong product instinct: ability to write crisp PRDs, define success metrics, and contribute customer insight back into product roadmap. Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
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